1. Papers presenting¶

1 16:23 - 16:52 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
2 16:54 - 17:07 Mukul Vishwas Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks link: https://arxiv.org/abs/1703.10593. presentation
3 17:08 - 17:20 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
4 17:20 - 17:45 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
5 17:45 - 17:56 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
6 17:57 - 18:08 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
7 18:08 - 18:26 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
8 18:26 - 18:41 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

Recorded video: https://www.youtube.com/watch?v=98GHEYSROFo