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] | |
Week of Nov 2 | 1 | |||||
Week of Nov 2 | 2 | |||||
Week of Nov 2 | 3 | |||||
Week of Nov 2 | 4 | |||||
Week of Nov 2 | 5 | |||||
Week of Nov 2 | Syed Saad Naseem | 6 | Learning The Difference That Makes A Difference With Counterfactually-Augmented Data | https://openreview.net/pdf?id=Sklgs0NFvr | ||
Week of Nov 9 | Donya Hamzeian | 7 | The Curious Case of Neural Text Degeneration | https://iclr.cc/virtual_2020/poster_rygGQyrFvH.html | ||
Week of Nov 9 | Parsa Torabian | 8 | Orthogonal Gradient Descent for Continual Learning | Paper | ||
Week of Nov 9 | Arash Moayyedi | 9 | When Does Self-supervision Improve Few-shot Learning? | Paper | ||
Week of Nov 9 | Parsa Ashrafi Fashi | 10 | Probabilistic Model-Agnostic Meta-Learning | Paper | ||
Week of Nov 9 | Jaskirat Singh Bhatia | 11 | A FAIRCOMPARISON OFGRAPHNEURALNETWORKSFORGRAPHCLASSIFICATION | Paper | ||
Week of Nov 9 | Gaurav Sikri | 12 | EMPIRICAL STUDIES ON THE PROPERTIES OF LINEAR REGIONS IN DEEP NEURAL NETWORKS | Paper | ||
Week of Nov 16 | Abhinav Jain | 13 | The Logical Expressiveness of Graph Neural Networks | Paper | ||
Week of Nov 16 | Gautam Bathla | 14 | One-Shot Object Detection with Co-Attention and Co-Excitation | Paper | ||
Week of Nov 16 | Shikhar Sakhuja | 15 | SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems | Paper | ||
Week of Nov 16 | Cameron Meaney | 16 | Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations | Paper | ||
Week of Nov 16 | Sobhan Hemati | 17 | Adversarial Fisher Vectors for Unsupervised Representation Learning | Paper | ||
Week of Nov 16 | Milad Sikaroudi | 18 | Domain Genralization via Model Agnostic Learning of Semantic Features | Paper | ||
Week of Nov 23 | Bowen You | 19 | DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION | Paper | ||
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 | Paper | placeholder |