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Evgeniy Pavlovskiy, 2023-02-16 13:55

Seminar "Big Data Analytics & Artificial Intelligence"

(sorted by later first)

Schedule 2022, Spring

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

March, 2023

Date Content Recording
2, Martirosyan S. Paper
Litvinenko D. Paper
9, Khubiev K. Paper
16, Boldinov A. Paper
Kamenev V. Paper
Motorin K. Paper
23, Redko A. Paper
30, Khubiev K. Thesis

April, 2023

Date Content Recording
6,
13,
20, Martirosyan S. Thesis
Motorin K. Thesis
Litvinenko D. Thesis
27, Boldinov A. Thesis
Kamenev V. Thesis
Redko A. Thesis

May, 2023

Date Content Recording
4,
11, Coursework defence
18,
25,

Schedule 2022, Autumn

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~

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~

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~

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~

Schedule 2022, Spring

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

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.

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)

Schedule 2021, Winter

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~

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)

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~

Schedule 2021, spring

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

June, 2021

4, ~25 min slot~
~25 min slot~
~25 min slot~
~25 min slot~

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)

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)

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)

February, 2021

9, Planning the semester
16, Planning the semester
~25 min slot~
~25 min slot~
23, Holiday

Schedule 2020, fall

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

September, 2020

8, #3879 Planning the semester
15, #3898 Invited lecture: Anton Kolonin, scientific topics for master
Planning the semester
22, #4005 Invited lecture: Dmitry Tailakov, scientific topics for master, Enterprise Practice from DFT, and from SDAML NSU
Planning the semester
29, #4100 Evgeniy Pavlovskiy @euxsun. Topics for master thesis.
Planning the semester

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.

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.

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)

Schedule 2020, spring

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

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

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

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

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.

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~

Schedule 2019, fall

Thursday, 18:10, cab 5239 NSU new building

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

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

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

September, 2019

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

Presented:
  1. Taylakov D. (Digital Field Technology)
  2. Kolonin A.
  3. Okunev A.
  4. Usov E. (NNTC.pro)
To be presented:
  1. ... see https://trello.com/b/859tElZm/scientfic-advisors-19-21

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

Schedule 2019, spring
Thursday, 16:20, cab 5212 NSU new building

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

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)

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

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

Schedule 2018, fall
Thursday, 18:10, cab 5273 NSU new building

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

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

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

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

  1. Taylakov D.
  2. Savostyanov A.N.
  3. Duchkov A.
  4. Golovin S.
  5. Pavlovskiy E.
  6. Kohanovskiy A.
  7. Sviridenko D.
  8. Redyuk A.
  9. Vityaev E.

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