# Difference between revisions of "stat940F21"

From statwiki

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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 30 || Wenjuan Qi || 31|| Network Deconvolution || [https://openreview.net/pdf?id=rkeu30EtvS Paper] || placeholder|| | |Week of Nov 30 || Wenjuan Qi || 31|| Network Deconvolution || [https://openreview.net/pdf?id=rkeu30EtvS Paper] || placeholder|| | ||

|- | |- | ||

+ | |Week of Nov 30|| Mohammad Mahmoud || 31||Electrocardiogram heartbeat classification based on a deep convolutional neural network and focal loss|| [https://www.sciencedirect.com/science/article/abs/pii/S0010482520302237] || |- |

## Revision as of 14:39, 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 | |

Week of Nov 30 | Mohammad Mahmoud | 31 | Electrocardiogram heartbeat classification based on a deep convolutional neural network and focal loss | [5] | - |