stat940F21

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		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]	Do not review
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