stat940F21
Project Proposal
Record your contributions here [1]
Use the following notations:
P: You have written a summary/critique on the paper.
T: You had a technical contribution on a paper (excluding the paper that you present).
E: You had an editorial contribution on a paper (excluding the paper that you present).
Paper presentation
Date | Name | Paper number | Title | Link to the paper | Link to the summary | Link to the video |
Sep 15 (example) | Ri Wang | Sequence to sequence learning with neural networks. | Paper | Summary | [2] | |
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Week of Nov 23 | Nouha Chatti | 20 | This Looks Like That: Deep Learning for Interpretable Image Recognition | Paper | ||
Week of Nov 23 | Mohan Wu | 21 | Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification | Paper | ||
Week of Nov 23 | Xinyi Yan | 22 | Incorporating BERT into Neural Machine Translation | Paper | ||
Week of Nov 23 | Meixi Chen | 23 | Functional Regularisation for Continual Learning with Gaussian Processes | Paper | ||
Week of Nov 23 | Ahmed Salamah | 24 | Sparse Convolutional Neural Networks | Paper | ||
Week of Nov 30 | Danial Maleki | 25 | Attention Is All You Need | Paper | ||
Week of Nov 30 | Gursimran Singh | 26 | BERTScore: Evaluating Text Generation with BERT. | Paper | ||
Week of Nov 30 | Govind Sharma | 27 | Time-series Generative Adversarial Networks | Paper | ||
Week of Nov 30 | Maral Rasoolijaberi | 28 | Parameter-free, Dynamic, and Strongly-Adaptive Online Learning | Paper | ||
Week of Nov 30 | Sina Farsangi | 29 | A Baseline for Few-Shot Image Classification | Paper | ||
Week of Nov 30 | Pierre McWhannel | 30 | [Pre-training Tasks for Embedding-based Large-scale Retrieval | https://iclr.cc/virtual_2020/poster_rkg-mA4FDr.html] | placeholder |