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|Week of Nov 9 || Jaskirat Singh Bhatia || 11|| A FAIRCOMPARISON OFGRAPHNEURALNETWORKSFORGRAPHCLASSIFICATION || [https://openreview.net/pdf?id=HygDF6NFPB Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=a_fair_comparison_of_graph_neural_networks_for_graph_classification Summary] || [https://drive.google.com/file/d/1Dx6mFL_zBAJcfPQdOWAuPn0_HkvTL_0z/view?usp=sharing Presentation] | |Week of Nov 9 || Jaskirat Singh Bhatia || 11|| A FAIRCOMPARISON OFGRAPHNEURALNETWORKSFORGRAPHCLASSIFICATION || [https://openreview.net/pdf?id=HygDF6NFPB Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=a_fair_comparison_of_graph_neural_networks_for_graph_classification Summary] || [https://drive.google.com/file/d/1Dx6mFL_zBAJcfPQdOWAuPn0_HkvTL_0z/view?usp=sharing Presentation] | ||
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|Week of Nov 9 || Gaurav Sikri || 12|| BREAKING CERTIFIED DEFENSES: SEMANTIC ADVERSARIAL EXAMPLES WITH SPOOFED ROBUSTNESS CERTIFICATES || [https://openreview.net/pdf?id=HJxdTxHYvB Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Breaking_Certified_Defenses:_Semantic_Adversarial_Examples_With_Spoofed_Robustness_Certificates Summary] || [[https://drive.google.com/file/d/1amkWrR8ZQKnnInjedRZ7jbXTqCA8Hy1r/view?usp=sharing Presentation ]] | |Week of Nov 9 || Gaurav Sikri || 12|| BREAKING CERTIFIED DEFENSES: SEMANTIC ADVERSARIAL EXAMPLES WITH SPOOFED ROBUSTNESS CERTIFICATES || [https://openreview.net/pdf?id=HJxdTxHYvB Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Breaking_Certified_Defenses:_Semantic_Adversarial_Examples_With_Spoofed_Robustness_Certificates Summary] || [[https://drive.google.com/file/d/1amkWrR8ZQKnnInjedRZ7jbXTqCA8Hy1r/view?usp=sharing Presentation ]] | ||
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|Week of Nov 16 || Abhinav Jain || 13|| The Logical Expressiveness of Graph Neural Networks || [http://www.openreview.net/pdf?id=r1lZ7AEKvB Paper] || || | |Week of Nov 16 || Abhinav Jain || 13|| The Logical Expressiveness of Graph Neural Networks || [http://www.openreview.net/pdf?id=r1lZ7AEKvB Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=THE_LOGICAL_EXPRESSIVENESS_OF_GRAPH_NEURAL_NETWORKS Summary] || [https://drive.google.com/file/d/1mZVlF2UvJ2lGjuVcN5SYqBuO4jZjuCcU/view?usp=sharing Presentation] | ||
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|Week of Nov 16 || Gautam Bathla || 14|| One-Shot Object Detection with Co-Attention and Co-Excitation || [https://papers.nips.cc/paper/8540-one-shot-object-detection-with-co-attention-and-co-excitation.pdf Paper] || || | |Week of Nov 16 || Gautam Bathla || 14|| One-Shot Object Detection with Co-Attention and Co-Excitation || [https://papers.nips.cc/paper/8540-one-shot-object-detection-with-co-attention-and-co-excitation.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=One-Shot_Object_Detection_with_Co-Attention_and_Co-Excitation Summary] || [https://drive.google.com/file/d/1OUx64_pTZzCQAdo_fmy_9h9NbuccTnn6/view?usp=sharing Presentation] | ||
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|Week of Nov 16 || Shikhar Sakhuja || 15|| SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems || [https://papers.nips.cc/paper/8589-superglue-a-stickier-benchmark-for-general-purpose-language-understanding-systems.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=SuperGLUE Summary] || [[https://youtu.be/5h-365TPQqE Presentation ]] | |Week of Nov 16 || Shikhar Sakhuja || 15|| SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems || [https://papers.nips.cc/paper/8589-superglue-a-stickier-benchmark-for-general-purpose-language-understanding-systems.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=SuperGLUE Summary] || [[https://youtu.be/5h-365TPQqE Presentation ]] | ||
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|Week of Nov 16 ||Milad Sikaroudi|| 18||Domain Genralization via Model Agnostic Learning of Semantic Features||[https://papers.nips.cc/paper/8873-domain-generalization-via-model-agnostic-learning-of-semantic-features.pdf Paper]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Model_Agnostic_Learning_of_Semantic_Features Summary]|| [https://youtu.be/djrJG6pJaL0 video] also available on Learn | |Week of Nov 16 ||Milad Sikaroudi|| 18||Domain Genralization via Model Agnostic Learning of Semantic Features||[https://papers.nips.cc/paper/8873-domain-generalization-via-model-agnostic-learning-of-semantic-features.pdf Paper]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Model_Agnostic_Learning_of_Semantic_Features Summary]|| [https://youtu.be/djrJG6pJaL0 video] also available on Learn | ||
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|Week of Nov 23 ||Bowen You|| 19||DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION||[https://openreview.net/pdf?id=S1lOTC4tDS Paper]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=DREAM_TO_CONTROL:_LEARNING_BEHAVIORS_BY_LATENT_IMAGINATION Summary] || | |Week of Nov 23 ||Bowen You|| 19||DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION||[https://openreview.net/pdf?id=S1lOTC4tDS Paper]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=DREAM_TO_CONTROL:_LEARNING_BEHAVIORS_BY_LATENT_IMAGINATION Summary] || Learn | ||
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|Week of Nov 23 ||Nouha Chatti|| 20|| This Looks Like That: Deep Learning for Interpretable Image Recognition||[https://papers.nips.cc/paper/9095-this-looks-like-that-deep-learning-for-interpretable-image-recognition.pdf Paper]|| || | |Week of Nov 23 ||Nouha Chatti|| 20|| This Looks Like That: Deep Learning for Interpretable Image Recognition||[https://papers.nips.cc/paper/9095-this-looks-like-that-deep-learning-for-interpretable-image-recognition.pdf Paper]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=This_Looks_Like_That:_Deep_Learning_for_Interpretable_Image_Recognition#Source_code Summary] || | ||
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|Week of Nov 23 || Mohan Wu || 21|| Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification || [https://proceedings.icml.cc/static/paper_files/icml/2020/807-Paper.pdf Paper] || || | |Week of Nov 23 || Mohan Wu || 21|| Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Cluster for Extreme Multi-label Text Classification || [https://proceedings.icml.cc/static/paper_files/icml/2020/807-Paper.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Extreme_Multi-label_Text_Classification Summary] || [https://www.youtube.com/watch?v=jG57QgY71yU video] | ||
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|Week of Nov 23 || Xinyi Yan || 22|| Dense Passage Retrieval for Open-Domain Question Answering || [https://arxiv.org/abs/2004.04906 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Dense_Passage_Retrieval_for_Open-Domain_Question_Answering Summary] || | |Week of Nov 23 || Xinyi Yan || 22|| Dense Passage Retrieval for Open-Domain Question Answering || [https://arxiv.org/abs/2004.04906 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Dense_Passage_Retrieval_for_Open-Domain_Question_Answering Summary] || Learn | ||
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|Week of Nov 23 || Meixi Chen || 23|| Functional Regularisation for Continual Learning with Gaussian Processes || [https://arxiv.org/pdf/1901.11356.pdf Paper] || || | |Week of Nov 23 || Meixi Chen || 23|| Functional Regularisation for Continual Learning with Gaussian Processes || [https://arxiv.org/pdf/1901.11356.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Functional_regularisation_for_continual_learning_with_gaussian_processes Summary]|| Learn | ||
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|Week of Nov 23 || Ahmed Salamah || 24|| AdaCompress: Adaptive Compression for Online Computer Vision Services || [https://arxiv.org/pdf/1909.08148.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Adacompress:_Adaptive_compression_for_online_computer_vision_services Summary] || | |Week of Nov 23 || Ahmed Salamah || 24|| AdaCompress: Adaptive Compression for Online Computer Vision Services || [https://arxiv.org/pdf/1909.08148.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Adacompress:_Adaptive_compression_for_online_computer_vision_services Summary] || [https://youtu.be/D54qsSkqryk video] or Learn | ||
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|Week of Nov 23|| Mohammad Mahmoud || 32||Mathematical Reasoning in Latent Space|| [https://iclr.cc/virtual_2020/poster_Ske31kBtPr.html?fbclid=IwAR2TQkabQkOzGcMl6bEJYggq8X8HIUoTudPIACX2v_ZT2LteARl_sPD-XdQ] || || | |Week of Nov 23|| Mohammad Mahmoud || 32||Mathematical Reasoning in Latent Space|| [https://iclr.cc/virtual_2020/poster_Ske31kBtPr.html?fbclid=IwAR2TQkabQkOzGcMl6bEJYggq8X8HIUoTudPIACX2v_ZT2LteARl_sPD-XdQ] || || | ||
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|Week of Nov 30 ||Danial Maleki || 25|| | |Week of Nov 30 ||Danial Maleki || 25||RoBERTa: A Robustly Optimized BERT Pretraining Approach ||[https://openreview.net/forum?id=SyxS0T4tvS Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Roberta Summary] || [https://youtu.be/JdfvvYbH-2s Presentation Video] | ||
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|Week of Nov 30 ||Gursimran Singh || 26||BERTScore: Evaluating Text Generation with BERT | |Week of Nov 30 ||Gursimran Singh || 26||BERTScore: Evaluating Text Generation with BERT||[https://openreview.net/pdf?id=SkeHuCVFDr Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=BERTScore:_Evaluating_Text_Generation_with_BERT Summary] || Learn | ||
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|Week of Nov 30 || Govind Sharma || 27|| Time-series Generative Adversarial Networks || [https://papers.nips.cc/paper/8789-time-series-generative-adversarial-networks.pdf Paper] || || | |Week of Nov 30 || Govind Sharma || 27|| Time-series Generative Adversarial Networks || [https://papers.nips.cc/paper/8789-time-series-generative-adversarial-networks.pdf Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Time-series_Generative_Adversarial_Networks Summary] || [https://youtu.be/SENjFF4N45s video] or Learn | ||
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|Week of Nov 30 ||Maral Rasoolijaberi|| 28|| | |Week of Nov 30 ||Maral Rasoolijaberi|| 28||A critical analysis of self-supervision, or what we can learn from a single image|| [https://openreview.net/pdf?id=B1esx6EYvr Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=CRITICAL_ANALYSIS_OF_SELF-SUPERVISION Summary]|| [https://youtu.be/HkkacHrvloE YouTube] | ||
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|Week of Nov 30 || Sina Farsangi || 29|| | |Week of Nov 30 || Sina Farsangi || 29|| Self-Supervised Learning of Pretext-Invariant Representations || [https://openaccess.thecvf.com/content_CVPR_2020/papers/Misra_Self-Supervised_Learning_of_Pretext-Invariant_Representations_CVPR_2020_paper.pdf Paper]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Self-Supervised_Learning_of_Pretext-Invariant_Representations Summary] || [https://www.youtube.com/watch?v=IlIPHclzV5E&ab_channel=sinaebrahimifarsangi YouTube] or Learn | ||
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|Week of Nov 30 || Pierre McWhannel || 30|| Pre-training Tasks for Embedding-based Large-scale Retrieval || [https://openreview.net/pdf?id=rkg-mA4FDr Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Pre-Training_Tasks_For_Embedding-Based_Large-Scale_Retrieval]|| | |Week of Nov 30 || Pierre McWhannel || 30|| Pre-training Tasks for Embedding-based Large-scale Retrieval || [https://openreview.net/pdf?id=rkg-mA4FDr Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Pre-Training_Tasks_For_Embedding-Based_Large-Scale_Retrieval Summary]|| Learn | ||
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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|| |
Revision as of 22:03, 5 December 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] | 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 | Summary | |
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 | Summary | video or Learn |
Week of Nov 30 | Maral Rasoolijaberi | 28 | A critical analysis of self-supervision, or what we can learn from a single image | Paper | Summary | YouTube |
Week of Nov 30 | Sina Farsangi | 29 | Self-Supervised Learning of Pretext-Invariant Representations | Paper | 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 |