Difference between revisions of "stat940F21"

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(Paper presentation)
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|Sep 15 (example)||Ri Wang || ||Sequence to sequence learning with neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Going_Deeper_with_Convolutions Summary] || [https://youtu.be/JWozRg_X-Vg?list=PLehuLRPyt1HzXDemu7K4ETcF0Ld_B5adG&t=539]
 
|Sep 15 (example)||Ri Wang || ||Sequence to sequence learning with neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Going_Deeper_with_Convolutions Summary] || [https://youtu.be/JWozRg_X-Vg?list=PLehuLRPyt1HzXDemu7K4ETcF0Ld_B5adG&t=539]
 
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|Week of Nov 2 ||   || 1|| ||   || ||
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|Week of Nov 2 || Jose Avilez || 1|| Gradientless Descent: High-Dimensional Zeroth-Order Optimisation || [https://openreview.net/pdf?id=Skep6TVYDB]  || ||
 
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|Week of Nov 2 ||  Abhinav Chanana || 2||AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity  || [https://openreview.net/pdf?id=S1gmrxHFvB Paper]  || ||
 
|Week of Nov 2 ||  Abhinav Chanana || 2||AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity  || [https://openreview.net/pdf?id=S1gmrxHFvB Paper]  || ||

Revision as of 13:42, 26 October 2020

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]
Week of Nov 2 Abhinav Chanana 2 AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity Paper
Week of Nov 2 Maziar Dadbin 3 ALBERT: A Lite BERT for Self-supervised Learning of Language Representations https://openreview.net/pdf?id=H1eA7AEtvS
Week of Nov 2 John Edwards 4 Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge Paper
Week of Nov 2 Wenyu Shen 5 STRUCTBERT:INCORPORATING LANGUAGE STRUCTURES INTO PRETRAINING FOR DEEP LANGUAGE UNDERSTANDING [4]
Week of Nov 2 Syed Saad Naseem 6 Learning The Difference That Makes A Difference With Counterfactually-Augmented Data Paper
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 Boosting Few-Shot Visual Learning with Self-Supervision https://openaccess.thecvf.com/content_ICCV_2019/papers/Gidaris_Boosting_Few-Shot_Visual_Learning_With_Self-Supervision_ICCV_2019_paper.pdf
Week of Nov 30 Pierre McWhannel 30 Pre-training Tasks for Embedding-based Large-scale Retrieval Paper placeholder
Week of Nov 30 Wenjuan Qi 31 Network Deconvolution Paper placeholder