Meeting #5616
Updated by Evgeniy Pavlovskiy over 3 years ago
h1. 1. Papers presenting
1 *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. "presentation":/attachments/download/3708
2 *Mukul Vishwas* Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks link: https://arxiv.org/abs/1703.10593. "presentation":/attachments/download/3706
3 *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. "presentation":/attachments/download/3707
4 *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. "presentation":/attachments/download/3709
5 *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. "presentation":/attachments/download/3712
6 *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) "presentation":/attachments/download/3710
7 *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) "presentation":/attachments/download/3711
8 *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. "presentation":/attachments/download/3712 "presentation":/attachments/download/3701
Recorded video: https://www.youtube.com/watch?v=98GHEYSROFo
1 *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. "presentation":/attachments/download/3708
2 *Mukul Vishwas* Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks link: https://arxiv.org/abs/1703.10593. "presentation":/attachments/download/3706
3 *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. "presentation":/attachments/download/3707
4 *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. "presentation":/attachments/download/3709
5 *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. "presentation":/attachments/download/3712
6 *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) "presentation":/attachments/download/3710
7 *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) "presentation":/attachments/download/3711
8 *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. "presentation":/attachments/download/3712 "presentation":/attachments/download/3701
Recorded video: https://www.youtube.com/watch?v=98GHEYSROFo