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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 Jose Avilez 1 Gradientless Descent: High-Dimensional Zeroth-Order Optimisation [3] GradientLess Descent GLD Presentation File:GradientLessDescent.pdf
Week of Nov 2 Abhinav Chanana 2 AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity Paper Summary [Presentation ]
Week of Nov 2 Maziar Dadbin 3 ALBERT: A Lite BERT for Self-supervised Learning of Language Representations paper Summary
Week of Nov 2 John Landon Edwards 4 From Variational to Deterministic Autoencoders Paper Summary Presentation
Week of Nov 2 Wenyu Shen 5 Pre-training of Deep Bidirectional Transformers for Language Understanding Paper Summary Presentation video
Week of Nov 2 Syed Saad Naseem 6 Learning The Difference That Makes A Difference With Counterfactually-Augmented Data Paper Summary Presentation video
Week of Nov 9 Donya Hamzeian 7 The Curious Case of Neural Text Degeneration Paper Summary
Week of Nov 9 Parsa Torabian 8 Orthogonal Gradient Descent for Continual Learning Paper Summary Learn
Week of Nov 9 Arash Moayyedi 9 When Does Self-supervision Improve Few-shot Learning? Paper Summary Learn
Week of Nov 9 Parsa Ashrafi Fashi 10 Learning to Generalize: Meta-Learning for Domain Generalization Paper Summary Presentation Video
Week of Nov 9 Jaskirat Singh Bhatia 11 A FAIRCOMPARISON OFGRAPHNEURALNETWORKSFORGRAPHCLASSIFICATION Paper Summary Presentation
Week of Nov 9 Gaurav Sikri 12 BREAKING CERTIFIED DEFENSES: SEMANTIC ADVERSARIAL EXAMPLES WITH SPOOFED ROBUSTNESS CERTIFICATES Paper Summary [Presentation ]
Week of Nov 16 Abhinav Jain 13 The Logical Expressiveness of Graph Neural Networks Paper Summary Presentation
Week of Nov 16 Gautam Bathla 14 One-Shot Object Detection with Co-Attention and Co-Excitation Paper Summary Presentation
Week of Nov 16 Shikhar Sakhuja 15 SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Paper Summary [Presentation ]
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 Summary Learn
Week of Nov 16 Sobhan Hemati 17 Adversarial Fisher Vectors for Unsupervised Representation Learning Paper Summary video
Week of Nov 16 Milad Sikaroudi 18 Domain Genralization via Model Agnostic Learning of Semantic Features Paper Summary video also available on Learn
Week of Nov 23 Bowen You 19 DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION Paper Summary Learn
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 Summary video
Week of Nov 23 Xinyi Yan 22 Dense Passage Retrieval for Open-Domain Question Answering Paper Summary Learn
Week of Nov 23 Meixi Chen 23 Functional Regularisation for Continual Learning with Gaussian Processes Paper Summary Learn
Week of Nov 23 Ahmed Salamah 24 AdaCompress: Adaptive Compression for Online Computer Vision Services Paper Summary video or Learn
Week of Nov 23 Mohammad Mahmoud 32 Mathematical Reasoning in Latent Space [4]
Week of Nov 30 Danial Maleki 25 RoBERTa: A Robustly Optimized BERT Pretraining Approach Paper Summary Presentation Video
Week of Nov 30 Gursimran Singh 26 BERTScore: Evaluating Text Generation with BERT Paper Summary Learn
Week of Nov 30 Govind Sharma 27 Time-series Generative Adversarial Networks Paper
Week of Nov 30 Maral Rasoolijaberi 28 A critical analysis of self-supervision, or what we can learn from a single image Paper Summary
Week of Nov 30 Sina Farsangi 29 Self-Supervised Learning of Pretext-Invariant Representations [5] Summary YouTube or Learn
Week of Nov 30 Pierre McWhannel 30 Pre-training Tasks for Embedding-based Large-scale Retrieval Paper Summary Learn
Week of Nov 30 Wenjuan Qi 31 Network Deconvolution Paper placeholder