Scientific workshop "Big Data Analytics"

h1. Seminar "Big Data Analytics & Artificial Intelligence"

(sorted by later first)

h2. Schedule 2024, Spring

h3. March, 2024

|_.Date|_.Content|_.Recording|

|7, |Deep Learning for ECG Classification||

|14, |Deep Contextualized Word Representations||

|21, |Sequence to sequence learning with neural networks||

|28, |AN IMAGE IS WORTH 16X16 WORDS||

h3. April, 2024

|_.Date|_.Content|_.Recording|

|4, |Deep Residual Learning for Image Recognition (Hou Zhengao)||

|11, |Deep Reinforcement Learning with Double Q-learning (Gao Zihan, )||

|18, |CLIP-Driven-Universal-Model||

|25, |Thesis/Coursework. All||

h3. May, 2024

|_.Date|_.Content|_.Recording|

|16, |Courseworks. 1st year students||

|23, |Coursework defence||

|30, |||

h2. Schedule 2023, Autumn

h3. September, 2023

|_.Date|_.Content|_.Recording|

|14, |Planning||

|21, |Finalizing paper selection, [[Papers2023]]||

|28, |||

h3. October, 2023

|_.Date|_.Content|_.Recording|

|5, |*Li Heng*. Paper|https://youtu.be/dbEbel4GpcQ|

|12, |-*Paksyutkin Artem*. Paper- (Moved to Nov-2)

*Hou Zhenghao*. Paper|https://youtu.be/XK2x9LMvO8c?si=3m3duFWWTPJ4l_f7&t=7023|

|19, |*Satrov Mikhail*. Paper|https://youtu.be/9qo0WyI8z7Y?si=Wm_WGh0LKZGAJLHj&t=5980|

|26, |*Quianyi Huang*. Paper|https://www.youtube.com/watch?v=1PIg4VOGgRc|

h3. November, 2023

|_.Date|_.Content|_.Recording|

|2, |-*Hou Zhenghao*. Paper- (Switched with Artem) *Paksyutkin Artem*. Paper|https://www.youtube.com/watch?v=ggQ41Deq_pM|

|9, |*Zihan Gao*. Paper|https://www.youtube.com/watch?v=kjnDk0MRDaU|

|16, |-*JiangFeng Cai*. Paper- (Not presented)|-|

|23, |*Hou Zhenghao*. Thesis

*Lai Xifei*. Paper|https://youtu.be/GL8G0v8Lufo?si=NmCKZprjLiFSMtwI&t=3148|

|30, |-*Anna Redko*. Paper- (Moved to the next week)

*Dmitry Litvinenko*. Paper

-*Jiangfeng Cai*. Thesis- (Not presented)|https://www.youtube.com/watch?v=Rt12RwOC3wc|

h3. December, 2023

|_.Date|_.Content|_.Recording|

|7, |-*Li Heng*. Thesis- (Not presented)

*Dmitry Litvinenko*. Thesis

-*Anna Redko*. Paper- (not presented)|https://www.youtube.com/watch?v=iD5Wz6izkNU|

|14, |~*Paksyutkin Artem*. Thesis

*Satrov Mikhail*. Thesis

*Lai Xifei*. Thesis~

(All moved to the next week)||

|21, |*Quianyi Huang*. Thesis

*Zihan Gao*. Thesis

-*Anna Redko*. Thesis- (not presented)

*Anna Redko*. Paper (moved from 7-Dec)

*Paksyutkin Artem*. Thesis

*Satrov Mikhail*. Thesis

*Lai Xifei*. Thesis|https://www.youtube.com/watch?v=zKHjf1oGgjo|

|28, |Examination week||

15 days * 2

h2. Schedule 2023, Spring

h3. February, 2023

|_.Date|_.Content|_.Recording|

|9, |||

|16, |

Video

1. data2vec https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language (by Evegniy Pavlovskiy)

2. alpha matting: http://ai.googleblog.com/2022/01/accurate-alpha-matting-for-portrait.html (by Evegniy Pavlovskiy)

3. code generation from OpenAI https://cdn.openai.com/papers/Formal_Mathematics_Statement_Curriculum_Learning__ICML_2022.pdf (by Evegniy Pavlovskiy)

4. qulacs https://github.com/qulacs/qulacs , Please cite this arXiv paper: https://arxiv.org/abs/2011.13524 (by Evegniy Pavlovskiy)

5. arcface loss https://arxiv.org/abs/1801.07698 (by Mikhail Liz)

6. Deep Learning for ECG Classification citation 86 , year 2017 https://iopscience.iop.org/article/10.1088/1742-6596/913/1/012004 (by Enes Kuzucu)

7. Airbnb Price Prediction Using MachineLearning and Sentiment Analysis  https://arxiv.org/abs/1907.12665 citation 13 , year 2019 (by Enes Kuzucu)

8. Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning. https://arxiv.org/abs/1801.07756 2018, citation 312 (by Enes Kuzucu)

9. Swin Transformer V2: Scaling Up Capacity and Resolution https://arxiv.org/abs/2111.09883 citations 5, 2021 (SOTA) (by Mikhail Liz)

10. YOLOv4: Optimal Speed and Accuracy of Object Detection link: https://arxiv.org/pdf/2004.10934.pdf. (by Alexander Rusnak)

11. Cut Mix (for data augmentation, related to master Khue Luu) https://openaccess.thecvf.com/content_ICCV_2019/papers/Yun_CutMix_Regularization_Strategy_to_Train_Strong_Classifiers_With_Localizable_Features_ICCV_2019_paper.pdf

12. Speed up Training with Variable Length Inputs by Efficient Batching Strategies  https://www.isca-speech.org/archive/interspeech_2021/ge21_interspeech.html ( f.e. Tacotron-2, by Anton Legchenko)

13. Financial Time Series Prediction Using Deep Learning (16) 2018 	https://github.com/xrndai/DeepDayTrade (from Virgilio Espina)

14. Financial Trading as a Game: A Deep Reinforcement Learning Approach (37) 2018 	https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning (from Virgilio Espina)

15. Trading via Image Classification (15) 2019 	https://github.com/ZacharyHimmelberger/image-classification-for-technical-indicators (from Virgilio Espina)

16. Spark NLP: Natural Language Understanding at Scale (11) 2021 	https://github.com/JohnSnowLabs/spark-nlp (from Virgilio Espina)

17. Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (171) 2017 	https://github.com/microsoft/qlib (from Virgilio Espina)

18. Inductive Graph Neural Networks for Spatiotemporal Kriging (18) 2020 	https://arxiv.org/abs/2006.07527 	https://github.com/Kaimaoge/IGNNK (from Virgilio Espina)

19. Graph Neural Networks in TensorFlow and Keras with Spektral (70) 2020 	https://arxiv.org/pdf/2006.12138.pdf 	https://github.com/danielegrattarola/spektral (from Virgilio Espina)

20. How Powerful are Graph Neural Networks? (2142) 2018 https://arxiv (from Virgilio Espina)

21. N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting     https://arxiv.org/pdf/2201.12886v2.pdf    https://github.com/cchallu/n-hits (from Alex Barnard)

22. FinRL: Deep Reinforcement Learning for Quantitative Finance https://arxiv.org/abs/2011.09607v1 Cited by 16 (From Abhishek Saxena)

23. https://arxiv.org/abs/2109.01652v5 Finetuned Language Models Are Zero-Shot Learners (by Maria Matveeva)

24. https://arxiv.org/abs/2005.12320v2 SCAN: Learning to Classify Images without Labels (by Maria Matveeva)

25. https://arxiv.org/pdf/2004.02349v2.pdf TAPAS: Weakly Supervised Table Parsing via Pre-training (by Maria Matveeva)

26. https://arxiv.org/pdf/2109.07958v1.pdf TruthfulQA: Measuring How Models Mimic Human Falsehoods (by Maria Matveeva)

27.YOLOX: Exceeding YOLO Series in 2021 (https://arxiv.org/abs/2107.08430) (by Hami Ismail)

28. Mask RCNN (https://arxiv.org/abs/1703.06870)  (by Hami Ismail)

29. Efficient Object Detection in Large Images Using Deep Reinforcement Learning (http://openaccess.thecvf.com/content_WACV_2020/papers/Uzkent_Efficient_Object_Detection_in_Large_Images_Using_Deep_Reinforcement_Learning_WACV_2020_paper.pdf)  (by Hami Ismail)

30. Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network (https://arxiv.org/abs/2003.09085)  (by Hami Ismail)

31. AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects (https://arxiv.org/pdf/1811.08728.pdf) (by Hami Ismail)||

|23, |Holiday||

h3. March, 2023

|_.Date|_.Content|_.Recording|

|2, |-Martirosyan S. Paper- (Withdrawn)

-Litvinenko D. Paper- (Moved to 23-Mar)||

|9, |Khubiev K. Paper||

|16, |Boldinov A. Paper

Kamenev V. Paper

-Motorin K. Paper-||

|23, |-Redko A. Paper- (moved to next)

Litvinenko D. Paper (moved from 2-Mar) ||

|30, |Khubiev K. Thesis

Tolstokulakov B. Paper

Redko A. Paper

Litvinenko D. Paper

Motorin K. Paper||

h3. April, 2023

|_.Date|_.Content|_.Recording|

|6, |||

|13, |Values Seminar - optional||

|20, |-Martirosyan S. Thesis-

Motorin K. Thesis

Litvinenko D. Thesis

Tolstokulakov B. Thesis||

|27, |Boldinov A. Thesis

Kamenev V. Thesis

Redko A. Thesis||

h3. May, 2023

|_.Date|_.Content|_.Recording|

|4, ||

|11, |Coursework defence||

|18, ||

|25, |||

h2. Schedule 2022, Autumn

h3. September, 2022

|1, |Introduction to MS|

|8, |Planning|

|15, |Planning|

|22, |Planning. https://www.youtube.com/watch?v=9J46UjvAdwg|

|29, |~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

h3. October, 2022

|6, |no lesson|

|13, |*Vladimir Kamenev*. Paper

*Artem Boldinov*. Paper

-*Anna Redko*. Paper- (Moved to 17 Nov)

~~25 min slot~~|

|20, |*Kirill Motorin*. Paper

*Kasymkhan Khubiev*. Paper

*Dmitry Litvinenko*. Paper

~~25 min slot~~|

|27, |-*Anastasia Suslenkova*. Paper- (moved to 3 Nov)

-*Syuzanna Martirosyan*. Paper- (Moved to 3 Nov)

~~25 min slot~~

~~25 min slot~~|

h3. November, 2022

|3, |-*Daria Fomicheva*. Paper- (Moved to 10 Nov)

*Anastasia Kalinina*. Paper

*Anastasia Suslenkova*. Paper (Moved from 27 Oct)

-*Syuzanna Martirosyan*. Paper- (Moved from 27 Oct, moved to 17 Nov)|

|10, |-*Daria Fomicheva*. Paper- (Moved from 3 Nov, moved to 17 Nov)

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|17, |*Boris Tolstokulakov*. Paper

-*Evgeniy Pavlovskiy*. Paper- (Moved to 24 Nov)

-*Sergey Pnev*. Review of Quantum ML Advantages topic.- (Deduced)

-*Syuzanna Martirosyan*. Paper- Not presented (Moved twice from 27 Oct and 3 Nov)

*Daria Fomicheva*. Paper (Moved twice from 3 Nov and 10 Nov)

*Anna Redko*. Paper (Moved from 13 Oct)|

|24, |*Evgeniy Pavlovskiy*. Paper (Moved from 17 Nov)

*Syuzanna Martirosyan*. Paper (Moved thrice from 27 Oct, 3 Nov, and 17 Nov)

~~25 min slot~~

~~25 min slot~~|

h3. December, 2022

|1, |~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|8, |*Anastasia Suslenkova*. Thesis.

*Daria Fomicheva*. Thesis

-*Boris Tolstokulakov*. Diploma-

-*Syuzanna Martirosyan*. Thesis-

*Anastasia Kalinina*. Thesis

*Dmitry Litvinenko*. Thesis|

|15, |-*Kasymkhan Khubiev*. Diploma-

*Anna Redko*. Thesis

*Kirill Motorin*. Thesis

*Vladimir Kamenev*. Thesis

*Artem Boldinov*. Thesis

*Anastasia Kalinina*. Thesis|

|22, |*Kasymkhan Khubiev*. Diploma (moved from previous week)

*Syuzanna Martirosyan*. Thesis (moved thrice)

*Boris Tolstokulakov*. Diploma (moved from 2 weeks back)

~~25 min slot~~|

h2. Schedule 2022, Spring

h3. February, 2022

|_.Date|_.Content|_.Recording|

|10, |Planning|https://www.youtube.com/watch?v=JHNyHxhfucc|

|17, |Planning

Video

1. data2vec https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language (by Evegniy Pavlovskiy)

2. alpha matting: http://ai.googleblog.com/2022/01/accurate-alpha-matting-for-portrait.html (by Evegniy Pavlovskiy)

3. code generation from OpenAI https://cdn.openai.com/papers/Formal_Mathematics_Statement_Curriculum_Learning__ICML_2022.pdf (by Evegniy Pavlovskiy)

4. qulacs https://github.com/qulacs/qulacs , Please cite this arXiv paper: https://arxiv.org/abs/2011.13524 (by Evegniy Pavlovskiy)

5. arcface loss https://arxiv.org/abs/1801.07698 (by Mikhail Liz)

6. Deep Learning for ECG Classification citation 86 , year 2017 https://iopscience.iop.org/article/10.1088/1742-6596/913/1/012004 (by Enes Kuzucu)

7. Airbnb Price Prediction Using MachineLearning and Sentiment Analysis  https://arxiv.org/abs/1907.12665 citation 13 , year 2019 (by Enes Kuzucu)

8. Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning. https://arxiv.org/abs/1801.07756 2018, citation 312 (by Enes Kuzucu)

9. Swin Transformer V2: Scaling Up Capacity and Resolution https://arxiv.org/abs/2111.09883 citations 5, 2021 (SOTA) (by Mikhail Liz)

10. YOLOv4: Optimal Speed and Accuracy of Object Detection link: https://arxiv.org/pdf/2004.10934.pdf. (by Alexander Rusnak)

11. Cut Mix (for data augmentation, related to master Khue Luu) https://openaccess.thecvf.com/content_ICCV_2019/papers/Yun_CutMix_Regularization_Strategy_to_Train_Strong_Classifiers_With_Localizable_Features_ICCV_2019_paper.pdf

12. Speed up Training with Variable Length Inputs by Efficient Batching Strategies  https://www.isca-speech.org/archive/interspeech_2021/ge21_interspeech.html ( f.e. Tacotron-2, by Anton Legchenko)

13. Financial Time Series Prediction Using Deep Learning (16) 2018 	https://github.com/xrndai/DeepDayTrade (from Virgilio Espina)

14. Financial Trading as a Game: A Deep Reinforcement Learning Approach (37) 2018 	https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning (from Virgilio Espina)

15. Trading via Image Classification (15) 2019 	https://github.com/ZacharyHimmelberger/image-classification-for-technical-indicators (from Virgilio Espina)

16. Spark NLP: Natural Language Understanding at Scale (11) 2021 	https://github.com/JohnSnowLabs/spark-nlp (from Virgilio Espina)

17. Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (171) 2017 	https://github.com/microsoft/qlib (from Virgilio Espina)

18. Inductive Graph Neural Networks for Spatiotemporal Kriging (18) 2020 	https://arxiv.org/abs/2006.07527 	https://github.com/Kaimaoge/IGNNK (from Virgilio Espina)

19. Graph Neural Networks in TensorFlow and Keras with Spektral (70) 2020 	https://arxiv.org/pdf/2006.12138.pdf 	https://github.com/danielegrattarola/spektral (from Virgilio Espina)

20. How Powerful are Graph Neural Networks? (2142) 2018 https://arxiv (from Virgilio Espina)

21. N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting     https://arxiv.org/pdf/2201.12886v2.pdf    https://github.com/cchallu/n-hits (from Alex Barnard)

22. FinRL: Deep Reinforcement Learning for Quantitative Finance https://arxiv.org/abs/2011.09607v1 Cited by 16 (From Abhishek Saxena)

23. https://arxiv.org/abs/2109.01652v5 Finetuned Language Models Are Zero-Shot Learners (by Maria Matveeva)

24. https://arxiv.org/abs/2005.12320v2 SCAN: Learning to Classify Images without Labels (by Maria Matveeva)

25. https://arxiv.org/pdf/2004.02349v2.pdf TAPAS: Weakly Supervised Table Parsing via Pre-training (by Maria Matveeva)

26. https://arxiv.org/pdf/2109.07958v1.pdf TruthfulQA: Measuring How Models Mimic Human Falsehoods (by Maria Matveeva)

27.YOLOX: Exceeding YOLO Series in 2021 (https://arxiv.org/abs/2107.08430) (by Hami Ismail)

28. Mask RCNN (https://arxiv.org/abs/1703.06870)  (by Hami Ismail)

29. Efficient Object Detection in Large Images Using Deep Reinforcement Learning (http://openaccess.thecvf.com/content_WACV_2020/papers/Uzkent_Efficient_Object_Detection_in_Large_Images_Using_Deep_Reinforcement_Learning_WACV_2020_paper.pdf)  (by Hami Ismail)

30. Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network (https://arxiv.org/abs/2003.09085)  (by Hami Ismail)

31. AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects (https://arxiv.org/pdf/1811.08728.pdf) (by Hami Ismail)|https://www.youtube.com/watch?v=5GxfxBey8Vs|

|24, |Planning, papers assignment|https://www.youtube.com/watch?v=xN71JgQELaE|

h3. March, 2022

|_.Date|_.Content|_.Recording|

|10, | *Andrey Yashkin*. Master thesis: Development of a compact speech recognition system for mobile devices using a narrowed dictionary.|https://www.youtube.com/watch?v=GwbhKfkBX8w|

|17, |*Anton Legchenko*. Speed up Training with Variable Length Inputs by Efficient Batching Strategies https://www.isca-speech.org/archive/interspeech_2021/ge21_interspeech.html

~~25 min slot~~

~~25 min slot~~|https://www.youtube.com/watch?v=sIrtOCSobOY|

|24, |*Sergey Garmaev*.  Accurate Alpha Matting for Portrait Mode Selfies on Pixel 6 (January 24, 2022): http://ai.googleblog.com/2022/01/accurate-alpha-matting-for-portrait.html

-*Alix Bernard*.  N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting https://arxiv.org/pdf/2201.12886v2.pdf https://github.com/cchallu/n-hits- (Moved to 14.04.2022)

*Enes Kuzucu*.  Deep Learning for ECG Classification citation 86 , year 2017 https://iopscience.iop.org/article/10.1088/1742-6596/913/1/012004

*Khue Luu*.  CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features https://openaccess.thecvf.com/content_ICCV_2019/papers/Yun_CutMix_Regularization_Strategy_to_Train_Strong_Classifiers_With_Localizable_Features_ICCV_2019_paper.pdf

*Khue Luu*. Master thesis: Brain Tumor Classification With Additional Semantic Features||

|31, |

*Alexander Rusnak*.  YOLOv4: Optimal Speed and Accuracy of Object Detection link: https://arxiv.org/pdf/2004.10934.pdf.||

h3. April, 2022

|_.Date|_.Content|_.Recording|

|7, |*Sergey Pnev*.  Qulacs: a fast and versatile quantum circuit simulator for research purpose https://github.com/qulacs/qulacs,  https://arxiv.org/abs/2011.13524

*Sergey Pnev*. Thesis

*Alix Bernard*. Thesis|https://www.youtube.com/watch?v=_6PME6_dEMU|

|14, |-*Mikhail Liz*.  Swin Transformer V2: Scaling Up Capacity and Resolution https://arxiv.org/abs/2111.09883 citations 5, 2021 (SOTA)- (Student withdrew the report)

-*Alexander Rusnak*. Thesis- (Moved to the next week)

*Alix Bernard*.  N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting https://arxiv.org/pdf/2201.12886v2.pdf https://github.com/cchallu/n-hits (Moved from March)

*Hami Ismail*. data2vec https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language

*Hami Ismail*. Thesis|https://www.youtube.com/watch?v=Mw_lLKFmPfU|

|21, |*Alexander Rusnak*. Thesis (Moved from 14.04.2022)

*Maria Matveeva*. SCAN: Learning to Classify Images without Labels https://arxiv.org/abs/2005.12320v2 

*Maria Matveeva*. Thesis

-*Mikhail Liz*. Thesis- (Student withdrew the report)

-*Sergey Garmaev*. Thesis- (Moved to 28.04.2022)

*Sergey Berezin*.  Code generation from OpenAI https://cdn.openai.com/papers/Formal_Mathematics_Statement_Curriculum_Learning__ICML_2022.pdf

*Enes Kuzucu*. Thesis

-*Abhishek Saxena*.  FinRL: Deep Reinforcement Learning for Quantitative Finance https://arxiv.org/abs/2011.09607v1 Cited by 16- (Moved to the next week)

-*Virgilio Espina*.  Financial Time Series Prediction Using Deep Learning (16) 2018 https://github.com/xrndai/DeepDayTrade- (Pushed to present the next week)|https://www.youtube.com/watch?v=BJeOmgD1Oxo|

|28, |*Sergey Berezin*. Thesis

*Virgilio Espina*.  Financial Time Series Prediction Using Deep Learning (16) 2018 https://github.com/xrndai/DeepDayTrade (pushed from the previous week)

*Virgilio Espina*. Thesis

*Abhishek Saxena*. Thesis

*Abhishek Saxena*.  FinRL: Deep Reinforcement Learning for Quantitative Finance https://arxiv.org/abs/2011.09607v1 Cited by 16 (Moved from 21.04.2022)

*Anton Legchenko*. An experience of Novosibirsk University SuperComputer Center usage for deep neural networks training. Usage issues.

*Sergey Garmaev*. Thesis (Moved from 21.04.2022)||

h2. Schedule 2021, Winter

h3. October, 2021

|7, |Planning|

|14, |Khue Luu, UNETR: Transformers for 3D Medical ImageSegmentation

Sergey Garmaev. Thesis

~~25 min slot~~

~~25 min slot~~|

|21, |~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|28, |Hami, thesus

Maria Matveeva, paper

~~25 min slot~~

~~25 min slot~~|

h3. November, 2021

|4, |Sergey Pnev. Paper

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|11, |Enes Kuzucu. Paper

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|18, |Khue Luu, Thesis (moved th the next class)

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|25, |-Sergey Pnev. Thesis- (Moved to the next)

Khue Luu, Thesis

Maria Matveeva, Thesis

-Sergey Garmaev. Paper- (Moved to the next time)

-Kirill Lunev. Paper- (Academic vacation)|

h3. December, 2021

|2, |-Virgilio. Paper- (Moved to the next time)

-Kirill Lunev. Thesis- (Academic vacation)

Anton Legchenko. Paper.

-Abhishek Saxena. Paper- (Moved to the next time)

-Sergey Garmaev. Paper (Moved from the previous time)- (Moved to the next time)

-Sergey Pnev. Thesis (Moved from the previous)- (Moved to the next time)|

|9, |-Hami. Paper- (Moved to 23-Dec)

Mukhtar. Paper

Abhishek Saxena. -Paper- Thesis (Moved from the previous time)

Sergey Garmaev. Paper (Moved from the previous time twice)

Sergey Pnev. Thesis (Moved from the previous time twice)

Virgilio. Paper (Moved from the previous time)|

|16, |Enes Kuzucu. Thesis

Abhishek Saxena. Paper (not ready, Moved to the next time)

Virgilio. Thesis (Moved to the next time)

Enes Kuzucu. Paper. Reproducing results|

|23, |Hami. Paper (Moved from 9-Dec)

Virgilio. Thesis (Moved from the previous time)

Abhishek Saxena. Paper (Moved from the previous time)

~~25 min slot~~|

h2. Schedule 2021, spring

Tuesday, 16:20 (NOVST GMT+7), online: https://us02web.zoom.us/j/84661660578?pwd=MHg0OXliZTRQV2xNZWJTVUx6QjM5UT09

h3. June, 2021

|4, |~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

h3. May, 2021

|4, #5637|-*Alexander Rusnak*. Thesis: Investigation of the possibility of generating neural network models for the generation of thematically and stylistically conditioned texts for low-resource languages / Исследование возможности создания нейросетевых моделей для генерации тематически и стилистически обусловленных текстов для малоресурсных языков.- (Postponed to uncertain date)

*Svetlana Kuchuganova*. Bachelor: Применение Mixup-Breakdown алгоритма для улучшения диаризации дикторов / Applying Mixup-Breakdown algorithm for speaker diarization improvement.

*Mukul Wishvas*. Thesis: Recognition, feature space representation, tracking, and performance enhancement in DCNN driven safety systems. / Распознавание, представление пространства функций, отслеживание и повышение производительности в системах безопасности, управляемых DCNN. (Moved from 18 May)

*Walid Koliai*. Thesis (1st year): Управляемая данными онлайн оценка смещений 2D изображения частиц с использованием графического процессора / Data driven online assessment of 2D particle image displacements using GPU.

-*Dinesh Yerukalareddy*. Thesis: Brain Tumor Classification from MRI Images using CNN with Extensive Data Augmentation / Классификация опухолей головного мозга по изображениям МРТ с использованием CNN с расширенной аугментацией данных.- (Moved to 18 May, switched with Mukul)

*Raphael Blankson*. Thesis: Applying Variational Circuits in Deep Learning Architectures for Improving Discriminative Power of  Speaker Identification Embeddings / Применение вариационных схем в архитектурах глубокого обучения для усиления дискриминативных свойств вложений в задаче идентификации дикторов.

*Maxim Kochanov*. Bachelor: Применение алгоритмов сегментации опухолей головного мозга для предсказания состояния пациентов / Applying brain tumor segmentation algorithms to predict patients state.

*Kozinets Roman*. Thesis: Analysis of CNN working with logical decision functions in the task of computer tomography images recognition / Анализ работы сети глубокого обучения с использованием логических решающих функций на примере задачи распознавания изображений компьютерной томографии. (Moved from 20 April)|

|11, #5759|*Kirill Kalmutskiy*. Thesis: Training of deep neural networks with incomplete training information on the example of recognition of tomographic images / Обучение глубоких нейросетей при неполной обучающей информации на примере распознавания томографических изображений.

-*Sayed Mohammad Sajjadi*. Thesis (1st year): Нахождение и изучение лидеров мнений в социальных медиа / Finding and studying opinion leaders in social media.- (Postponed to uncertain date)

-*Mikhail Rodin*. Thesis: Investigation of the possibility of constructing neural network models for thematically and stylistically determined poetic texts / Исследование возможности построения пораждающих нейросетевых моделей для тематически и стилистически обусловленных поэтических текстов.- (Postponed to uncertain date)

*Oladotun Aluko*. Thesis: Studying applicability of Proof-of-Reputation as an alternative consensus mechanism for Distributed Ledger Systems / Исследование применимости "доказательства права репутацией" как альтернативного механизма обеспечения консенсуса для систем распределенного реестра.

-*Rishab Tiwari*. Thesis: Online tool for linguistic and sociolinguistic studies accessing open online resources / Онлайн инструмент для проведения лингвистического и социолингвистического исследования с привлечением открытых онлайн ресурсов.- (Moved to 25 May, exchange with Watana)

*Watana Pongsapas*. Thesis: Deep learning-based Machine Vision for the Task of Grasping Chemical Hardware. (Moved from 25 May)

*Mark Baushenko*. Bachelor: Исследование алгоритмов синтеза русской речи, основанных на увеличении разрешения спектрограмм / Russian speech synthesis algorithms investigatoin based on spectrogram superresolution.|

|18, #5723|*Daria Pirozhkova*. Thesis: Study of methods for automatic taxonomy enrichment.

*Enes Kuzucu*. Thesis (1st year): Оценка среднего времени отклика парадигмы стоп-сигнала по сигналам электроэнцефалографии (ЭЭГ) / Estimating average response time for Stop-signal paradigm from Electroencephalography (EEG) signals.

*Nikita Nikolaev*. Thesis: Zero-shot learning approach to the problem of short text classification.

-*Sergey Verbitskiy*. Bachelor: Разработка алгоритма распознавания звуков с использованием ансамбля сверточных нейронных сетей / Sounds recognition algorithm development based on convolutional neural networks ensemble.- (Not appeared)

-*Mukul Wishvas*. Thesis: Recognition, feature space representation, tracking, and performance enhancement in DCNN driven safety systems. / Распознавание, представление пространства функций, отслеживание и повышение производительности в системах безопасности, управляемых DCNN.- (Moved to 4 May)

*Dinesh Yerukalareddy*. Thesis: Brain Tumor Classification from MRI Images using CNN with Extensive Data Augmentation / Классификация опухолей головного мозга по изображениям МРТ с использованием CNN с расширенной аугментацией данных.

*Kaivalya Pandey*. Thesis: Improving sentiment analysis for stock trends prediciton / Улучшение анализа тональности для предсказания трендов на бирже.|

|25, #5769|*Khue Luu*. Thesis (1st year): Сегментаций опухолей мозга на основе 3D-Unet / Brain Tumor Segmentation with 3D-UNet.

*Alexey Korolev*. Thesis: Generalized zero-shot learning for intent classification and slot filling.

*Mikhail Liz*. Thesis: Quantitative processing of scanning probe microscopy image with deep learning techniques.

*Watana Pongsapas*. Galaxy detection and identification using deep learning and data augmentation link: https://www.sciencedirect.com/science/article/abs/pii/S2213133718300325, reproducible: https://github.com/astroCV/astroCV.

-*Watana Pongsapas*. Thesis: Deep learning-based Machine Vision for the Task of Grasping Chemical Hardware.- (Moved to 11 May, exchange with Rishabh)

*Rishab Tiwari*. Thesis: Online tool for linguistic and sociolinguistic studies accessing open online resources / Онлайн инструмент для проведения лингвистического и социолингвистического исследования с привлечением открытых онлайн ресурсов. (Moved from 11 May)

-*Alix Bernard*. Thesis: Enhancement of Turbulence Models by Machine Learning Techniques.- (Moved to uncertained date)

*Vasiliy Baranov*. Thesis: Classification of COVID-19 in Computed Tomography using Deep Neural Networks. (Moved from 30 March)|

h3. April, 2021

|6, |[Optional] Data Scientist - values and functions of a professional|

|13, #5601|*Sergey Verbitskiy*. wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations link: https://arxiv.org/pdf/2006.11477.pdf.

-*Oladotun Aluko*. Depth-Aware Video Frame Interpolation link: https://arxiv.org/pdf/1904.00830.pdf, reproducible: https://github.com/baowenbo/DAIN/.- (Moved back to 29 March)

*Rishabh Tiwari*. ResNeSt: Split-Attention Networks link: https://arxiv.org/pdf/2004.08955.pdf, reproducible: https://github.com/zhanghang1989/ResNeSt.

*Mark Baushenko*. WaveGlow: A Flow-based Generative Network for Speech Synthesis link: https://arxiv.org/abs/1811.00002v1, reproducible: https://github.com/NVIDIA/waveglow.

-*Dinesh Reddy*. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks link: https://arxiv.org/abs/1511.06434, reproducible: https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/dcgan.- (Moved to April 27)

*Maria Matveeva*. Thesis (1st year): Обнаружение текстовых связей с использованием методов иерархической кластеризации / Text relation detection using hierarchical clustering techniques.

*Andrey Yashkin*. A U-Net Based Discriminator for Generative Adversarial Networks link: https://arxiv.org/pdf/2002.12655.pdf, reproducible: https://github.com/boschresearch/unetgan.

*Vladislav Panferov*. Master thesis: Recognition of Rocks Lithology on the Images of Core Samples

-*Mohammed Nasser* (Moved from 29 March)- (Moved to 20 April)

*Daria Pirozhkova*. SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing link: https://arxiv.org/pdf/1808.06226v1.pdf, reproducible: https://github.com/google/sentencepiece (Moved from 20 April)|

|20 #5775|-*Daria Pirozhkova*. SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing link: https://arxiv.org/pdf/1808.06226v1.pdf, reproducible: https://github.com/google/sentencepiece-

-*Kirill Kalmutskiy*. Wide & Deep Learning for Recommender Systems link: https://arxiv.org/abs/1606.07792, reproducible: https://github.com/shenweichen/DeepCTR.- (Moved to next time)

*Alexey Korolev*. Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data link: https://arxiv.org/abs/1909.06312, reproducible: https://github.com/Qwicen/node.

-*Mikhail Liz*. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks link: https://arxiv.org/abs/1506.01497, reproducible: https://github.com/facebookresearch/detectron2.- (Discarded as student took acad.vacation)

-*Sayed Mohammad*. Opinion leader detection using whale optimization algorithm in online social network link: https://www.sciencedirect.com/science/article/pii/S095741741930733X?casa_token=Sj6ySbKY5j0AAAAA:mPgOKDf9RS_AzUACoTAH7G6uu9-gUy_R5E4l6p7j6p916VcGwykuBDZKhfWqsSOeRSRfQ-D6yA.-  (Moved to the next time)

-*Mikhail Rodin*. Paper.-

-*Kozinets Roman*. Thesis: Analysis of CNN working with logical decision functions in the task of computer tomography images recognition / Анализ работы сети глубокого обучения с использованием логических решающих функций на примере задачи распознавания изображений компьютерной томографии.- (Moved to 4 May)

*Sergey Garmaev*. SpectralNet: Spectral Clustering using Deep Neural Networks link: https://arxiv.org/abs/1801.01587, reproducible: https://github.com/kstant0725/SpectralNet

*Mohammed Nasser* Thesis: Enhancement of consistent depth estimation for monocular videos / Улучшение согласованной оценки глубины для монокулярных видео (Moved from 29 March, 13 April)|

|27, #5616|*Hami bin Ismail*. Thesis (1st year): Распознавание различных объектов нефтепромысловой инфраструктуры методами машинного обучения / Recognition of different objects of oilfield infrastructure by machine learning methods.

*Nikita Nikolaev*. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer link: https://arxiv.org/abs/1910.10683v3, reproducible: https://github.com/google-research/text-to-text-transfer-transformer.

*Mukul Vishwas*. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks link: https://arxiv.org/abs/1703.10593.

*Kaivalya Pandey*. Practical Deep Reinforcement Learning Approach for Stock Trading link: https://arxiv.org/pdf/1811.07522v2.pdf, reproducible: https://github.com/AI4Finance-LLC/FinRL-Library.

*Raphael Blankson*. The power of data in quantum machine learning link: https://arxiv.org/pdf/2011.01938v2.pdf, reproducible: https://github.com/prantik-pdeb/Quantum-Machine-Learning.

*Sergey Berezin*. Thesis (1st year): Анализ современных алгоритмов распознавания именованных сущностей и аннотирования текста / Analysis of modern algorithms for named entitiy recognition and text summarization.

*Dinesh Reddy*. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks link: https://arxiv.org/abs/1511.06434, reproducible: https://github.com/eriklindernoren/PyTorch-GAN/tree/master/implementations/dcgan. (Moved from 13 April)

*Kirill Kalmutskiy*. Wide & Deep Learning for Recommender Systems link: https://arxiv.org/abs/1606.07792, reproducible: https://github.com/shenweichen/DeepCTR. (Moved from 20 April)|

h3. March, 2021

|2, #5537|-Enes. Paper-

Svetlana Kuchuganova. Audio Super Resolution using Neural Networks link: https://arxiv.org/abs/1708.00853v1, reproducible:https://github.com/kuleshov/audio-super-res.

-Maxim Kochanov. Paper.-

-Vasiliy Baranov. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation link: https://arxiv.org/pdf/1612.00593v2.pdf, reproducible:https://github.com/charlesq34/pointnet.-

Hami Ismail. TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images link: https://arxiv.org/abs/2001.01469.|

|9, #5536|*Rohan Rapthore*. Enriching Pre-trained Language Model with Entity Information for Relation Classification link: https://arxiv.org/abs/1905.08284, reproducible:https://github.com/wang-h/bert-relation-classification.

*Alexander Rusnak*. The Effectiveness of Data Augmentation in Image Classification using Deep Learning link: https://arxiv.org/pdf/1712.04621.pdf, reproducible: https://github.com/kandluis/nn-data-augmentation.

*Maria Matveeva*. Fake News Detection on Social Media using Geometric Deep Learning link: https://arxiv.org/abs/1902.06673.

*Mohammed Sweilam*. Unsupervised Monocular Depth Estimation with Left-Right Consistency link: https://arxiv.org/pdf/1609.03677.pdf, reproducible: https://github.com/mrharicot/monodepth.

*Khue Luu*. MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentationS3D-UNet: Separable 3D U-Net for Brain Tumor Segmentation link: https://arxiv.org/abs/1902.04049, reproducible: https://github.com/nibtehaz/MultiResUNet.

*Enes Kuzucu*. Age and gender classification using brain–computer interface link: https://link.springer.com/article/10.1007/s00521-018-3397-1 (moved from 2 March)|

|16, #5532|-*Alexander Rusnak*. Report from previous time about the paper results reproducibility.-

*Vladislav Panferov*. ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing link: https://arxiv.org/abs/1902.07669, reproducible:https://github.com/allenai/scispacy

*Rohan Rathore*. Thesis: Explorative Study of Explainable Artificial Intelligence Techniquest for Sentiment Analysis Applied for English Language.

*Alix Bernard*. Gradient Centralization: A New Optimization Technique for Deep Neural Networks link: https://arxiv.org/pdf/2004.01461v2.pdf, reproducible:https://github.com/Yonghongwei/Gradient-Centralization

*Virgilio Espina*. Thesis (1st year): Применение искусственного интеллекта в прогнозировании вспышки лихорадки Денге на Филиппинах / Application of Artificial Intelligence in Predicting Dengue Outbreak in the Philippines.

*Sergey Pnev*. TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation link: https://arxiv.org/pdf/2102.04306v1.pdf, reproducible:https://github.com/Beckschen/TransUNet.

*Maxim Kochanov*. Image-to-Image Translation with Conditional Adversarial Networks link: https://arxiv.org/pdf/1611.07004.pdf, reproducible:https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix. (Moved from 2 March)|

|23, #5774|-*Vladislav Panferov*. Master thesis: Recognition of Rocks Lithology on the Images of Core Samples- (Moved to 13 April)

*Walid Koliai*. End to End Learning for Self-Driving Cars link: https://arxiv.org/abs/1604.07316, reproducible: https://github.com/SullyChen/Autopilot-TensorFlow.

*Vigrilio Espina*. Developing a dengue forecast model using machine learning: A case study in China link: shorturl.at/lwEFT.

*Sergey Berezin*. Big Bird: Transformers for Longer Sequences link: https://arxiv.org/abs/2007.14062v2, reproducible: https://github.com/google-research/bigbird.

*Kozinets Roman*. YOLOv4: Optimal Speed and Accuracy of Object Detection link: https://arxiv.org/pdf/2004.10934.pdf.

*Vasiliy Baranov*. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation link: https://arxiv.org/pdf/1612.00593v2.pdf, reproducible: https://github.com/charlesq34/pointnet. (Moved from 2 March)

-*Alexander Rusnak*. Report from previous time about the paper results reproducibility. (Moved from 16 March)- (Moved to 30 March)

*Alix Bernard*. Report from previous time about the paper results reproducibility. (Moved from 16 March)|

|30, #5773|-*Mohammed Sweilam*. Thesis: Enhancement of consistent depth estimation for monocular videos / Улучшение согласованной оценки глубины для монокулярных видео- (Moved to 13 April)

*Oladotun Aluko*. Depth-Aware Video Frame Interpolation link: https://arxiv.org/pdf/1904.00830.pdf, reproducible: https://github.com/baowenbo/DAIN/. (Moved from 13 April)

-*Alexander Donets*. Thesis: Automated thesaurus enrichment for the Russian Language using self-supervised deep learning approach.- (Postponed to uncertain date)

-*Alexander Donets*. FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP link: https://www.aclweb.org/anthology/N19-4010/, reproducible: https://github.com/flairNLP/flair.- (Postponed to uncertain date)

*Sergey Pnev*. Thesis (1st year): Алгоритм семантической сегментации томографических изображений с использованием DNN / Algorithm of semantic segmentation of tomographic images using DNN.

-*Vasiliy Baranov*. Thesis: Classification of COVID-19 in Computed Tomography using Deep Neural Networks.- (Moved to 25 May)

Vasiliy Baranov. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation link: https://arxiv.org/pdf/1612.00593v2.pdf, reproducible:https://github.com/charlesq34/pointnet. (Continue with reproducible report)

*Alexander Rusnak*. Report from previous time about the paper results reproducibility. (Moved twice from 16,23 March)|

h3. February, 2021

|9, |Planning the semester|

|16, |Planning the semester

~~25 min slot~~

~~25 min slot~~|

|23, |Holiday|

h2. Schedule 2020, fall

Tuesday, 16:20, online: https://zoom.us/j/86212050320

h3. September, 2020

|8, #3879|Planning the semester|

|15, #3898|Invited lecture: Anton Kolonin, "scientific topics for master":https://trello.com/c/AYkBULyA

Planning the semester|

|22, #4005|Invited lecture: Dmitry Tailakov, "scientific topics for master":https://trello.com/c/TQEQuTvs/4-dmitry-taylakov-phd, "Enterprise Practice from DFT, and from SDAML NSU":/issues/4005

Planning the semester|

|29, #4100|Evgeniy Pavlovskiy @euxsun. "Topics for master thesis":https://trello.com/c/eRW2rCoI/5-evgeniy-pavlovskiy-phd.

Planning the semester|

h3. October, 2020

|6, #4197|Sergey Berezin. Towards a Human-like Open-Domain Chatbot https://arxiv.org/abs/2001.09977.

Nikita Nikolaev. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks - IJCNLP 2019 - cited by 194. https://paperswithcode.com/paper/sentence-bert-sentence-embeddings-using.

Virgilio Espina. Reinforcement learning applied to Forex trading. https://bit.ly/33p4qXT.

Khue Luu. Generative Adversarial Networks https://arxiv.org/abs/1406.2661.

Vladislav Panferov. Progressive Semantic-Aware Style Transformation for Blind Face Restoration https://arxiv.org/pdf/2009.08709.pdf.|

|13, #4325|Daria Pirozhkova. OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction https://paperswithcode.com/paper/opennre-an-open-and-extensible-toolkit-for.

-Oladotun Aluko. Transformer-OCR https://github.com/fengxinjie/Transformer-OCR.- (moved due illnes of the reporter)

Dinesh Reddy. Community detection in social networks https://bit.ly/32u1jP2.

Kirill Lunev. Data mining with big data https://ieeexplore.ieee.org/abstract/document/6547630.

Walid Koliai. VoiceFilter from Google https://google.github.io/speaker-id/publications/VoiceFilter/.|

|20, #4448|Kaivalya Pandey. 3D Self-Supervised Methods for Medical Imaging https://arxiv.org/abs/2006.03829, https://paperswithcode.com/paper/3d-self-supervised-methods-for-medical.

Maria Matveeva. The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics https://arxiv.org/pdf/2002.09931v1.pdf.

Enes Kuzucu. Deep Learning Applications in Medical Image Analysis /2018/251cit https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8241753.

Andrey Yashkin. Semantic Image Synthesis with Spatially-Adaptive Normalization https://arxiv.org/abs/1903.07291.

Oladotun Aluko. Transformer-OCR https://github.com/fengxinjie/Transformer-OCR.|

|27, #4525|Rusnak Alexander. Neural oblivious decision ensembles for deep learning on tabular data https://arxiv.org/pdf/1909.06312.pdf, https://github.com/Qwicen/node.

Vladislav Panferov. Thesis: Recognition of Rocks Lithology on the Images of Core

Samples (Supervisor: Dmitry Tailakov).

Virgilio Espina. Thesis: Dengue Prediciton (Supervisor: Alexey Kolesnikov).

Ahmed Fakhry. Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers /2017/59 Cit. https://arxiv.org/pdf/1708.09757.pdf.

Vassily Baranov. Zero-Shot Learning - A ComprehensiveEvaluation of the Good, the Bad and the Ugly https://arxiv.org/pdf/1707.00600.pdf.|

h3. November, 2020

|3, #4622|Khue Luu. Thesis: Brain Tumor Segmentation (Sci.advisor: Evgeniy N. Pavlovskiy, PhD).

Mikhail Liz. Activate or Not: Learning Customized Activation https://arxiv.org/abs/2009.04759.

Enes Kuzucu. Thesis: EEG (Sci.advisor: Alexander N. Savostyanov, PhD)..

Aaron Xu Zhang. You Only Look Once: Unified, Real-Time Object Detection https://arxiv.org/abs/1506.02640 (and YOLO-5).

-Ahmed Fakhry. Thesis: ?.-

Watana Pongsapas. Automatic License Plate Recognition with Pyhton and OpenCV.|

|10, #4730|Alexey Korolev. Plug and Play Language Models: A Simple Approach to Controlled Text Generation https://arxiv.org/pdf/1912.02164.pdf.

Rishabh Tiwarri. Mask R-CNN https://arxiv.org/abs/1703.06870.

Kirill Kalmutskiy. XGBoost: A Scalable Tree Boosting System https://arxiv.org/pdf/1603.02754.pdf.

Hami Asmai. Predictive big data analytics for supply chain demand forecasting: methods, applications, and research opportunities https://journalofbigdata.springeropen.com/articles/10.1186/s40537-020-00329-2.

Vassily Baranov. Thesis: Classification of COVID-19 in Computed Tomography using Deep Neural Networks (Supervisor: V.B. Berikov).|

|17, #4731|Sayed Mohammad Sajjadi. Online actions with offline impact: How online social networks influence online and offline user behavior  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5361221/.

Alix Bernard. Field Inversion and Machine Learning With Embedded Neural Networks: Physics-Consistent Neural Network Training https://www.researchgate.net/publication/333808531_Field_Inversion_and_Machine_Learning_With_Embedded_Neural_Networks_Physics-Consistent_Neural_Network_Training.

Alexander Donets. Entity, Relation, and Event Extraction with Contextualized Span Representations https://paperswithcode.com/paper/entity-relation-and-event-extraction-with.

Sergey Pnev. Deep neural networks for youtube recommendations  https://research.google/pubs/pub45530.pdf.

Mikhail Rodin. Classification is a Strong Baseline for Deep Metric Learning https://arxiv.org/abs/1811.12649v2.|

|24, #4776|Mukul Vishvas. DeepFaceDrawing: Deep Generation of Face Images from Sketches https://research.fb.com/wp-content/uploads/2020/06/Neural-Supersampling-for-Real-time-Rendering.pdf.

Segery Berezin. Thesis: ?.

Mohammed Sweilam. Consistent Video Depth Estimation https://arxiv.org/abs/2004.15021.

-Watana Pongsapas. Automatic License Plate Recognition with Pyhton and OpenCV.- Moved to 3-Nov-2020

Raphael Blankson. A variational Algorithm for Quantum Neural Networks https://link.springer.com/chapter/10.1007/978-3-030-50433-5_45.|

h3. December, 2020

20 minutes for each presentation.

|1, #4873|Aaron Xu Zhang. Thesis: Social structure and dynamics mining for TikTok (social network may change). Supervisor: A.Kolonin.

Rohan Rathore. Does BERT Make Any Sense? https://arxiv.org/pdf/1909.10430.pdf

-Mikhail Rodin. Thesis: Investigation of the possibility of constructing neural network models for thematically and stylistically determined poetic texts. Supervirsor: V.B.Barakhnin, I.Bondarenko.- Not delivered.

-Sayed Mohammed Sajjadi. Thesis: ?. Supervisor: A.Kolonin.?- Moved to a next seminar

-Oladotun Aluko. Thesis: Studying Applicability of PoR as an alternative consensus mechanism for Distributed Ledger Systems. Supervisor: A.Kolonin.- Not delivered.

Walid Koliai. Thesis: 2D online GPU correlation analysis of streamed particle images. Supervisor: Mikhail Tokarev, PhD|

|8, #4965|Rohan Rathore. Thesis: Explorative study of explainable artificial intelligence technique for sentiment analysis applied for English language. Supervisor: A.Kolonin.

Kirill Kalmutskiy. Thesis: Training of deep neural networks with incomplete training information on the example of recognition of tomographic images. Supervisor: V. Berikov

Kirill Lunev. Thesis: . Supervisor: A. Kolonin

Mikhail Liz. Thesis: Quantitative processing of scanning probe microscopy image with deep learning techniques. Supervisor: A. Okunev

Rusnak Alexander. Thesis: Investigation of the possibility of generating neural network models for the generation of thematically and stylistically conditioned texts for low-resource languages. Supervisor: V. Barakhnin

Hami Ismail. Thesis: Recognition of different objects of oilfield infrastructure by machine learning methods. Supervisor: Dmitry Tailakov.

_Maxim Kochanov. DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation https://arxiv.org/pdf/2006.04868.pdf. (15 min)_

-_Mark Baushenko. Neural Supersampling for Real-time Rendering. (15 min)_- moved to the next week|

|15, #5110|-Kaivalya Pandey. Thesis.- Not ready.

Alix Bernard. Thesis.

Daria Pirozhkova. Thesis: Study of methods for automatic taxonomy enrichment for the Russian language. advisor: Batura T.

Mukul Vishwas. Thesis.

Andrey Yashkin. Thesis.

_Sergey Verbitsky. Residual Audio Neural Networks with Multiple Features for Sound Classification. (10 min)_

Sayed Mohammed Sajjadi. Thesis: ?. Supervisor: A.Kolonin. (moved from 1 Dec)

Oladotun Aluko. Thesis: Studying Applicability of PoR as an alternative consensus mechanism for Distributed Ledger Systems. Supervisor: A.Kolonin. (moved from 1 Dec)

_Mark Baushenko. Neural Supersampling for Real-time Rendering. (10 min)_ (moved from 8 Dec)|

|22, #|-Rishabh Tiwarri. Thesis.- Moved to the next week

Nikita Nikoaev. Thesis.

Alexey Koroloev. Thesis.

Watana Pongsapas. Thesis

Mohammed Sweilam. Thesis.

_Svelana Kuchuganova. Mixup Breakdown Algorithm. (15 min)_

Raphael Blankson. Thesis. (moved from the next week)|

|29, #5467|Sergey Pnev. Thesis.

Alexander Donets. Thesis.

Maria Matveeva. Thesis.

-Raphael Blankson. Thesis.- Moved to the previous week

Dinesh Reddy. Thesis.

Rishabh Tiwarri. Thesis. (moved from the previous week)|

h2. Schedule 2020, spring

Thursday, 16:20, -cab 0207 NSU new building, '-1' elevator floor-, online: https://zoom.us/j/910812617

h3. June, 2020

|4, #3424|*Elena Voskoboy* Coursework

*Abhishek Saxena* Coursework

*Vladislav Panferov* Traditional Method Inspired Deep Neural Network for Edge Detection

*Sergey Garmaev* Coursework

*Nikita Nikolaev* Coursework

*Owen Siyoto* Learning to interpret satellite images in global scale using wikipedia

*Mohamed Nasser* Coursework

*Watana Pongsapas* Coursework

*Alix Bernard* Coursework

*Andrey Yashkin* Coursework

*Thibault Kollen* Gogioso S. A Corpus-based Toy Model for DisCoCat //arXiv preprint arXiv:1605.04013. – 2016. URL: https://arxiv.org/pdf/1605.04013.pdf	

*Geoffroy de Felcourt* Shen J. et al. Natural tts synthesis by conditioning wavenet on mel spectrogram predictions //2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). – IEEE, 2018. – С. 4779-4783. URL: https://arxiv.org/pdf/1712.05884.pdf	

*Antoine Logeais* Skip-thoughts, Infersent, RandSent - Facebook

*Richard Fambon* Vorontsov K. et al. Bigartm: Open source library for regularized multimodal topic modeling of large collections //International Conference on Analysis of Images, Social Networks and Texts. – Springer, Cham, 2015. – С. 370-381. URL: http://www.machinelearning.ru/wiki/images/e/ea/Voron15aist.pdf	||

h3. May, 2020

|7, #3241|*Ravi Kumar* Master

*Owen Siyoto* Master

*Oladotun Aluko* Coursework

*Alexander Rusnak* Coursework

*Vladislav Panferov* Coursework

*Abhishek Saxena* Blockchain for AI: Review and open research challenges

*Mikhail Liz* Coursework|

|14, #3248|*Kaivalya Pandey* Coursework

*Andrey Yashkin* Coursework

*Rohan Rathore* Coursework

-*Sergey Garmaev* Coursework- rescheduled for June 4

*Dinesh Reddy* Coursework

-*Elena Voskoboy* Coursework- rescheduled for June 4

*Munyaradzi Njera* Paper

*Munyaradzi Njera* Master Thesis|

|21, #3283|*Daria Pirozhkova* Coursework

*Alexey Korolev* Coursework

*Mohamed Nasser* End-to-End 3D Face Reconstruction with Deep Neural Networks

-*Alexander Donets* Coursework- (academic vacation)

-*Rishabh Tiwari* Coursework- shifted to the next week

*Olga Yakovenko* Master thesis|

|28, #3325|-*Alix Bernard* Coursework- postponed to the next week

*Mukul Vishwas* Coursework

-*Watana Pongsapas* Coursework- postponed to the next week

*Raphael Blankson* Coursework

-*Nikita Nikolaev* Coursework- rescheduled for June, 4

-*Olga Yakovenko* Master thesis- (presented 21.05.2020)

*Rishabh Tiwari* Coursework|

h3. April, 2020

|2, #|[Optional] Daia Scientist - values of a professional|

|9 -2-, #3202|*Thibault Kollen* Flipout: Efficient pseudo-independent weight perturbations on mini-batches

*Richard Fambon* Tensor Networks

*Alexander Rusnak* GPT-2

*Dinesh Reddy* Brain Tumor Sementation Using Deep Learning by Type Specific Sorting of Images

*Alix Bernard* Deep Learning based Approach to Reduced Order Modelling

*Ravi Kumar* Complex Convolution. IEEE

*Olga Yakovenko* University of Pau|

|16 -9-, #3226|*Rohan Rathore* Layer-wise relevance propagation: an overview

*Antoine Logeais* Weight uncertainty in neural networks

-*Owen Siyoto* Learning to interpret satellite images in global scale using wikipedia-

*Alexey Korolev* Bert-dst: Scalable end-to-end dialogue state tracking with bidirectional encoder representations from transformer

*Alexander Donets* Implicit weight uncertainty in neural networks|

|23 -16-, #3225|*Jetina Tsvaki* Understanding mixup training methods

*Jetina Tsvaki* Master

*Mukul Vishwas* A Study on Face Recognition Techniques with Age and Gender Classification

*Rishabh Tiwari*

*Geoffroy de Felcourt* Jasper: An end-to-end convolutional neural acoustic model

*Fishman Daniil* XGBoost: A Scalable Tree Boosting System

*Fishman Daniil* Master

-*Mikhail Rodin* Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization-|

|30, #3240|*Raphael Blankson* Towards quantum machine learning with tensor networks 

*Vassily Baranov* Coursework

*Kalmutskiy Kirill* Coursework

-*Mikhail Liz* Coursework- (illness)

*Mikhail Rodin* Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization|

h3. March, 2020

|5, #3137|-*Elena Voskoboy* Hybrid VAE for NLG-

*Mikhail Liz* Deep learning for symbolic mathematics

*Vassily Baranov* Distilling knowledge

-*Andrey Yashkin*-

*Sergey Garmaev* Reservoir Computing|

|12, #3138|*Oladotun Aluko* NASNet and AutoML

*Watana Pongsapas*  Deep learning: A Generic approach for extreme condition traffic

*Kirill Kalmutsky* Variational Quantum Circuits and Deep Reinforcement Learning

*Andrey Yashkin* Quantum circuit learning|

|19, #3139|*-Geoffroy de Felcourt-*

*Elena Voskoboy* Hybrid VAE for NLG

~~25 min slot~~|

|26, #3190|*Omid Razizadeh* Reynolds Averaged Turbulence Modeling using Deep Neural Networks with Embedded Invariance.

*Omid Razizadeh* Master thesis

*Kaivalya Pandey* Deep Reinforcement Learning

-*Alix Bernard* Deep Learning based Approach to Reduced Order Modelling-.|

h3. February, 2020

|6, #3133|Planning the semester|

|13, #3133|Planning the semester|

|20, #3136|*Nikita Nikolaev* Zero and Few shot learning

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|27, #3135|*Daria Pirozhkova* ERNIE

-*Sergey Garmaev* Reservoir Computing-

~~25 min slot~~

~~25 min slot~~|

h2. Schedule 2019, fall

Thursday, 18:10, cab 5239 NSU new building

h3. December, 2019

|5, #2819|*Rohan Rahore* “Why Should I Trust You?” Explaining the Predictions of Any Classifier

*Jetina Tsvaki* Thesis

*Omid Razizadeh* Thesis

-*Mihail Rodin* Style transfer-

-*Mohammed Sweilam*-|

|12, #2860|*Ravi Kumar* Thesis

*Raphael Blankson*

*Nikita Nikolaev*

*Abhishek Saxena*

*Rishabh Tiwarri*|

|19, #2946|Conducted by *Kaivalya Anand Pandey*

*Jetina Tsvaki* Paper

-*Elizaveta Tagirova* Paper with code: Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme-

-*Elizaveta Tagirova* Master thesis-

-*Vladislav Panferov*-

*Mikhail Liz* CosFace

*Alexander Rusnak*|

|26, #|*Mihail Rodin* Style transfer

*Mohammed Sweilam*

-*Alexander Rusnak*-

*Owen Siyoto* Master thesis

*Owen Siyoto* Efficient Net

Rescheduled:

* *Elizaveta Tagirova* Paper with code: Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme-

* *Elizaveta Tagirova* Master thesis

* *Vladislav Panferov*|

h3. November, 2019

|7, #2660|*Sergey Garmaev*

*Dinesh Reddy*

*Daria Pirozhkova*

-*Oladotun Aluko*-

*Ravi Kumar* Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge|

|14, #2720|*Roman Kozinets*, Weight Agnostic Neural Networks

*Roman Kozinets*, Master thesis

*Elena Voskoboy* A neural algorithm of artistic style

*Alix Bernard*

-*Oladotun Aluko*-|

|21, #2726|*Kaivalya Pandey*

*Alexander Donets*

-*Rishabh Tiwari*-

*Andrey Yashkin*

*Oladotun Aluko*|

|28, #2766|*Alexey Korolev*

*Kirill Kalmutskiy*

*Mukul Vishwas*

*Antoine Kristanek*|

h3. October, 2019

|3, #2447|~~25 min slot~~

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|10, #2456|Scientific Advisor: prof. Yakovenko S.N.

Scientific Advisor: Postovalov S.N.

Scientific Advisor: Bondarenko I., Batura T.V.

~~25 min slot~~|

|17, #2473|*Munyaradzi Njera* Paper

~~25 min slot~~

~~25 min slot~~

~~25 min slot~~|

|24, #|Scientific Advisor: prof. Palchunov D.E.

*Munyaradzi Njera* Thesis

*Vassily Baranov*|

|31, #2638|*Omid Razizadeh*, Data-driven predictive using field inversion

~~25 min slot~~

*Watana Pongsapas*

-*Ravi Kumar* Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge-|

h3. September, 2019

1. Introduction

2. Scientific advisors presentations: https://trello.com/b/859tElZm/scientfic-advisors-19-21

Presented:

# Taylakov D. (Digital Field Technology)

# Kolonin A.

# Okunev A.

# Usov E. (NNTC.pro)

To be presented:

# ... see https://trello.com/b/859tElZm/scientfic-advisors-19-21

3. Planning the semester #2435 (20.09.2019, 26.09.2019)

h2. Schedule 2019, spring

Thursday, 16:20, cab 5212 NSU new building

h3. May, 2019

|23, #|*Munjaradzi Njera* Master thesis

*Andrey Marinov*: Selsam, D., Lamm, M., Bünz, B., Liang, P., de Moura, L., & Dill, D. L. (2018). Learning a SAT solver from single-bit supervision. arXiv preprint arXiv:1802.03685.

*Ravi Kumar* Course work

-*Klim Markelov* Master thesis-

*Roman Kozinets* Master thesis (imaging)

*Anton Dorozhko* Reinforcement Learning for long-term reward optimization in recommender systems (Master thesis)

*Omid Razizadeh* Coursework: Detecting Alzheimer's disease using different machine learning approaches

*Artem Sergeev* Paper: Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition

*Artem Sergeev* Master Thesis|

|16, #|*Jetina Tsvaki* Master thesis

*Anik Chakrabarthy* Master thesis

*Dylan Bersans* Outside the closed world: On Using ML for Network Intrusion Detection

*Andrey Marinov* Master thesis: Research on an efficiency of the bilingual model for the silent speech recognition.

*Ivan Rogalsky* Open System Categorical Quantum Semantics in NLP (master thesis, review)

*Jetina Tsvaki* Predicting Oil Movement in a development System Using Deep Latent Dynamic Models|

h3. April, 2019

|25, #|Open Seminar jointly with Open Data Science Siberia

*Andrey Zubkov* Master thesis: Separability of silent speech phonemes for English language. Speaker and session independence.

*Evgeniy Kurochkin* Master thesis

*Alexandra Luchkina* Master thesis

*Leyuan Sheng* Master thesis: Text to speech synthesis using Generative Adversarial networks for speech enhancement.

*Malysheva Anastasia* Master thesis: The development and research of the prediction methods for time series obtained by the combination of different patterns.

*Olga Yakovenko* Course work

*Juan Pinzon* Master thesis: Sentiment Analysis in Social Media Texts (Spanish language)

Video: https://www.youtube.com/watch?v=T7Oa4hBR3g4|

|18, #|-*Ivan Rogalsky* Open System Categorical Quantum Semantics in NLP (master thesis, review)

*Ravi Kumar* Master thesis

*Jetina Tsvaki* Predicting Oil Movement in a development System Using Deep Latent Dynamic Models

*Dylan Bersans* Outside the closed world: On Using ML for Network Intrusion Detection

*Olga Yakovenko* Course work

*Juan Pinzon* Master thesis- replaced by

*Natalia Loukashevich* Modern trends on NLP (Tochka Kipenia, Academpark, 16:00, 18.04.2019)|

|11, #2164|*Leyuan Sheng* Tacotron 2

-*Klim Markelov* Master thesis-

-*Juan Pinzon* Master thesis-

*Ravi Kumar* State of the art Deep Learning: Evolving Machine Intelligence Toward Tomorrow's

*Malysheva Anastasia* Attention is all you need https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf |

|4, #2146|*Roman Kozinets* CNN for speech command recognition. Review

-*Ivan Rogalsky* Quantum-Theoretic Approach in Dicstr. Semantics-

*Akilesh Sivaswamy* Master thesis: Data classification using superposition and HMM

*Madina Tussupova* Master Thesis: Determination of grammatical categories using machine learning algorithms

*Madina Tussupova* 5.3. Wieting J., Kiela D. No Training Required: Exploring Random Encoders for Sentence Classification //arXiv preprint arXiv:1901.10444. – 2019. URL (20 min)|

h3. March, 2019

|28, #2105|-*Ravi Kumar* State of the art Deep Learning: Evolving Machine Intelligence Toward Tomorrow's-

*Munjaradzi Njera* Human-level control through deep reinforcement learning

*Thomas Vialars* Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures

*Petr Gusev* MXNet

*Petr Gusev* Master Thesis|

|21, #2086|*Juan Pinzon* Universal Language Model Fine-tuning for Text Classification

*Elizaveta Tagirova* Master Thesis

-*Petr Gusev* MXNet-

-*Seth Gyamerah* Understanding consumer behavior-|

|14, #2076|*Omid Razizadeh* Pixel Recurrent Neural Networks.

*Klim Markelov* A Style-Based Generator Architecture for Generative Adversarial Networks.

*Anik Chakrabarthy* DisCoCat toy model

*Akilesh Sivaswamy* CosFace|

|7, #2071|-*Andrey Zubkov* Performance of Word Embeddings- (previously reported)

*Alexandra Luchkina* Triplet loss

*Evgeniy Kurochkin* Self-Taught Convolutional Neural Networks for Short Text Clustering

*Olga Yakovenko* BigARTM|

h3. February, 2019

|28, #2058|*Elizaveta Tagirova* Universal Sentence Encoder

*Andrey Zubkov* Neurohackathon on autism disorder: prized solution

~~time slot (25 min)~~

~~time slot (25 min)~~|

|21, #2054|*Vyacheslav Mukhortov* Project Management Practice: teambiudling and project tasks.

*Evgeniy Pavlovskiy* Planning of academic seminar for Spring, 2019|

h2. Schedule 2018, fall

Thursday, 18:10, cab 5273 NSU new building

h3. December, 2018

|6, #2034|*Leyuan Sheng*, CycleGAN

*Tagirova Elizaveta*. LIME (local interpretable model-agnostic explanations) https://arxiv.org/pdf/1602.04938v1.pdf

*Luchkina Alexandra*, Sobolev Training

*Fishman Daniil*, Prediction of enhancer-promoter interactions via natural language processing|

|13, #|*Anton Kolonin*. Topics for master work.

*Evgeniy Averyanov*, Schmidt, Mark. Minimizing finite sums with the stochastic average gradient / M. Schmidt, N. Le Roux, F. Bach // Mathematical Programming. — 2017. — Vol. 162(1). — P. 83–112. — URL: https://link.springer.com/article/10.1007/s10107-016-1030-6

*Polina Potapova*, XNOR-Net, https://arxiv.org/pdf/1603.05279.pdf

*Lee Wonjai*. Bayesian CDF (continue with example)

|

|20, #|-*Artem Sergeev*. ArcFace-

*Gyamerah Seth*, Fuzzy time series on financial forecasting

-*Mulley Loic*, Triplet Loss https://arxiv.org/pdf/1503.03832.pdf-

*Kurochkin Evgeniy*, DenseNet

|

|27, #|*Julien Machet*, Machine learning top down and bottom up.

*Ivan Rogalsky*

*Arsentiy Melnikov* Teacher student curriculum learning https://arxiv.org/pdf/1707.00183.pdf

*Loic Mulley*, Triplet Loss https://arxiv.org/pdf/1503.03832.pdf

*Artem Sergeev*, ArcFace|

h3. November, 2018

|1, #|*Petr Gusev*. ResNet, ResNeXt K. He, X. Zhang, S. Ren, and J. Sun. Deep Residual Learning for Image Recognition. In CVPR, 2016

*Anastasia Malysheva*, Variational Autoencoders

*Anik Chakrabarthy*. Quantum Semantics

~~25 min slot~~|

|8, #|*Akilesh Sivawamy*, Mobile NN.

*Lee Wonjai*. Bayesian CDF

-*Polina Potapova*, XNOR-Net, https://arxiv.org/pdf/1603.05279.pdf- (moved to December)

*Olga Yakovenko*, RNN for Speech Recognition|

|15, #|*Ravi Kumar*, Deep Learning in Mobile and Wireless Networks: a Survey

*Munjaradzi Njera*, Attentioned based LSTM

*Juan Fernando Pinzon Correa*, Rapids AI

*Urynbassarov Mukhtar*, GAN|

|22, #|lost|

|29, #|*Roman Kozinets*, Siamese NN

*Omid Razizadeh*, tSNE

*Jetina Tsvaki*, Natural language based financial forecasting: a survey

*Owen Siyoto*, Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|

h3. October, 2018

|18, #2028|Planning the semester|

|25, #|*Klim Markelov*, Capsule NN

*Andrey Zubkov*, Dynamic Word Embeddings https://arxiv.org/abs/1804.07983

*Vitaly Poteshkin*, MixUp

Planning the semester|

h3. September, 2018

1. 2nd year students coursework pre-defence: (1) #2008, (2) 14.09.2018.

2. Scientific advisors presentations: https://trello.com/b/ZlMTMsS8/bdaai-scientific-topics

# Taylakov D.

# Savostyanov A.N.

# Duchkov A.

# Golovin S.

# Pavlovskiy E.

# Kohanovskiy A.

# Sviridenko D.

# Redyuk A.

# Vityaev E.

h2. [[Archive]]