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== [[F20-STAT 946-Proposal| Project Proposal ]] ==
== [[F20-STAT 946-Proposal| Project Proposal ]] ==
= Record your contributions here [https://docs.google.com/spreadsheets/d/1Me_O000pNxeTwNGEac57XakecG1wahvwGE5n36DGIlM/edit?usp=sharing]=
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=
=Paper presentation=
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{| border="1" cellpadding="3"
{| border="1" cellpadding="3"
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|width="60pt"|Date
|width="120pt"|Date
|width="100pt"|Name  
|width="200pt"|Name  
|width="30pt"|Paper number  
|width="30pt"|Paper number  
|width="700pt"|Title
|width="900pt"|Title
|width="30pt"|Link to the paper
|width="30pt"|Link to the paper
|width="30pt"|Link to the summary
|width="30pt"|Link to the video
|width="30pt"|Link to the video
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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]
 
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|Week of Nov 8 ||  Abhinav Chanana (Example) || 1||AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity  || [https://openreview.net/pdf?id=S1gmrxHFvB Paper]  || [https://youtu.be/epBzlXHFNlY Presentation ]
|Week of Nov 2 ||  Jose Avilez || 1|| Gradientless Descent: High-Dimensional Zeroth-Order Optimisation || [https://openreview.net/pdf?id=Skep6TVYDB]  || [[GradientLess Descent]] || [https://uofwaterloo-my.sharepoint.com/:v:/g/personal/jlavilez_uwaterloo_ca/ETNogDRpwJlPjSo5o0EY53UBLC7f0zmR9--a0uz6GYN8zw?e=J8V0f3 GLD Presentation] [[File:GradientLessDescent.pdf|Slides]]
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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]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Augmix:_New_Data_Augmentation_method_to_increase_the_robustness_of_the_algorithm#Conclusion Summary] || [[https://youtu.be/epBzlXHFNlY Presentation ]]
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|Week of Nov 2 || Maziar Dadbin  || 3|| ALBERT: A Lite BERT for Self-supervised Learning of Language Representations || [https://openreview.net/pdf?id=H1eA7AEtvS paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=ALBERT:_A_Lite_BERT_for_Self-supervised_Learning_of_Language_Representations Summary]||
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|Week of Nov 2  ||John Landon Edwards || 4||From Variational to Deterministic Autoencoders  ||[http://www.openreview.net/pdf?id=S1g7tpEYDS Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=From_Variational_to_Deterministic_Autoencoders#Redesigned_Training_Loss_Function Summary] || [https://youtu.be/yW4eu3FWqIc Presentation]
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|Week of Nov 2  ||Wenyu Shen  || 5|| Pre-training of Deep Bidirectional Transformers for Language Understanding  || [https://arxiv.org/pdf/1810.04805.pdf Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=STAT946F20/BERT:_Pre-training_of_Deep_Bidirectional_Transformers_for_Language_Understanding Summary]  || [https://www.youtube.com/watch?v=vF5EoIFd2D8 Presentation video]
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|Week of Nov 2  ||  Syed Saad Naseem || 6||  Learning The Difference That Makes A Difference With Counterfactually-Augmented Data||  [https://openreview.net/pdf?id=Sklgs0NFvr Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Learning_The_Difference_That_Makes_A_Difference_With_Counterfactually-Augmented_Data Summary] || [https://youtu.be/bKC2BiTuSTQ Presentation video]
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|Week of Nov 9 || Donya Hamzeian  || 7|| The Curious Case of Neural Text Degeneration  ||  [https://iclr.cc/virtual_2020/poster_rygGQyrFvH.html Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=The_Curious_Case_of_Degeneration Summary] ||
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|Week of Nov 9 || Parsa Torabian  || 8|| Orthogonal Gradient Descent for Continual Learning || [http://proceedings.mlr.press/v108/farajtabar20a/farajtabar20a.pdf Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=orthogonal_gradient_descent_for_continual_learning Summary] || Learn
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|Week of Nov 9 ||  Arash Moayyedi || 9|| When Does Self-supervision Improve Few-shot Learning? || [https://openreview.net/forum?id=HkenPn4KPH Paper]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=When_Does_Self-Supervision_Improve_Few-Shot_Learning%3F Summary] || Learn
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|Week of Nov 9 ||  Parsa Ashrafi Fashi || 10|| Learning to Generalize: Meta-Learning for Domain Generalization  ||  [https://arxiv.org/pdf/1710.03463 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Meta-Learning_For_Domain_Generalization Summary]|| [https://youtu.be/b9MU5cc3-m0 Presentation Video]
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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]
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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 11 ||   || || || ||
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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]  || [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]
|Week of Nov 11 || Benyamin Jamialahmad || || Perceiver: General Perception with Iterative Attention || [https://arxiv.org/abs/2103.03206] ||[https://www.youtube.com/watch?v=NmzsUgfzor0] ||
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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] || [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]
|Week of Nov 11 ||   || || ||   ||
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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 11 ||   || ||  ||   ||
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|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 || [https://www.sciencedirect.com/science/article/pii/S0021999118307125 Paper] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Physics-informed_neural_networks:_A_deep_learning_framework_for_solving_forward_and_inverse_problems_involving_nonlinear_partial_differential_equations Summary] || Learn
|Week of Nov 11 ||   || || || ||
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|Week of Nov 16 ||Sobhan Hemati|| 17||Adversarial Fisher Vectors for Unsupervised Representation Learning||[https://papers.nips.cc/paper/9295-adversarial-fisher-vectors-for-unsupervised-representation-learning.pdf Paper]||[https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Adversarial_Fisher_Vectors_for_Unsupervised_Representation_Learning Summary] || [https://www.youtube.com/watch?v=WKUj30tgHfs&feature=youtu.be video]
|Week of Nov 11 ||   || || ||   ||
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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 18 || Veronica Salm || || StructBERT: Incorporating Language Structures Into Pre-Training for Deep Language Understanding || [https://openreview.net/pdf?id=BJgQ4lSFPH Paper] || [https://www.youtube.com/watch?v=WT2HD9Fv8-g Presentation] ||
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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] || Learn
|Week of Nov 18 || Youssef Fathi || || NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis || [https://arxiv.org/pdf/2003.08934 Paper] || [https://www.youtube.com/watch?v=MJ3DQgKZ8qg]  
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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]|| [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=This_Looks_Like_That:_Deep_Learning_for_Interpretable_Image_Recognition#Source_code Summary] ||
|Week of Nov 18 || Wei Liang || || Deep Stable Learning for Out-Of-Distribution Generalization (Received by CVPR2021) || [https://arxiv.org/pdf/2104.07876.pdf] ||[https://www.dropbox.com/s/hd770on5c0mmgo7/STAT940_PAPER_PRESENTATION.pdf%20-%20%5BDeep%20Stable%20Learning%20for%20Out-Of-Distribution%20Generalization%5D%20-%20SumatraPDF%202021-11-17%2014-08-58.mp4?dl=0]
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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] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Extreme_Multi-label_Text_Classification Summary] || [https://www.youtube.com/watch?v=jG57QgY71yU video]
|Week of Nov 18 || Taj Jones-McCormick  || ||Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
||https://papers.nips.cc/paper/2020/file/0a73de68f10e15626eb98701ecf03adb-Paper.pdf ||[https://www.youtube.com/watch?v=Asv1lMiHCw8]
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|Week of Nov 25 || Muhammad Maruf Sazed  || || An unsupervised deep learning approach for real-world image denoising|| https://openreview.net/pdf?id=tIjRAiFmU3y  ||https://drive.google.com/file/d/1BXnuezattSvxOK83FAfiLjKyQc8uKzpq/view?usp=sharing
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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] || Learn
|Week of Nov 25 || Yuxiang Huang || || Reliability Does Matter: An End-to-EndWeakly Supervised Semantic Segmentation Approach || [https://ojs.aaai.org//index.php/AAAI/article/view/6971 Publication] || [https://www.youtube.com/watch?v=DavSpJirihE&list=LLtF8FO4E2r-AE_mZNSVHZKA&ab_channel=Yuxiang Presentation]
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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]  || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Functional_regularisation_for_continual_learning_with_gaussian_processes Summary]|| Learn
|Week of Nov 25 || Yuliang Shi || || Small-gan: Speeding up gan training using core-sets || [http://proceedings.mlr.press/v119/sinha20b/sinha20b.pdf Paper]  || [https://uofwaterloo-my.sharepoint.com/:v:/g/personal/y323shi_uwaterloo_ca/EbfkKXoQamVMgSdQ8eCiQuYBoSg8kGBkF89qd47H2EjxlQ?e=GAK5kB Presentation]
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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] || [https://youtu.be/D54qsSkqryk video] or Learn
|Week of Nov 25 || Varnan Sarangian  || || Self-training For Few-shot Transfer Across Extreme Task Differences || [https://openreview.net/pdf?id=O3Y56aqpChA] || [https://youtu.be/a6Dh4JQfJPQ]
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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 25 || Alice Leung || ||ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators || [https://openreview.net/pdf?id=r1xMH1BtvB Paper]|| [https://youtu.be/mji9nBiwoU8 Presentation]  ||
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|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]
|Week of Nov 25 || Maryam Yalsavar || || Knowledge Extraction with No Observable Data || [http://papers.neurips.cc/paper/8538-knowledge-extraction-with-no-observable-data.pdf] || [https://www.youtube.com/watch?v=zsvN2tREiLE] ||
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|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
|Week of Nov 25 || Shervin Hakimi || || What Do Neural Networks Learn When Trained With Random Labels? || [https://proceedings.neurips.cc/paper/2020/file/e4191d610537305de1d294adb121b513-Paper.pdf] ||
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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] || [https://wiki.math.uwaterloo.ca/statwiki/index.php?title=Time-series_Generative_Adversarial_Networks Summary] || [https://youtu.be/SENjFF4N45s video] or Learn
|Week of Nov 25 || Islam Nasr || || Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters
|| [http://ceur-ws.org/Vol-2846/paper10.pdf] || [https://youtu.be/HP9zyxTOioA] ||
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|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]
|Week of Nov 25 || Jared Feng || || The Autoencoding Variational Autoencoder || https://nips.cc/virtual/2020/public/poster_ac10ff1941c540cd87c107330996f4f6.html ||
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|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
|Week of Nov 25 || Mina Kebriaee || || Synthesizer: Rethinking Self-Attention for Transformer Models ||[https://arxiv.org/pdf/2005.00743.pdf] || [https://encoded-bongo-ca-youseeu-com.s3.amazonaws.com/i-18270/class/_6WAX3WJ/_1168044/media/_as390938/__1168044_act-67315_44487daa95b5cb3f5fa11383b545f45a.mp4] ||
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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 Summary]|| Learn
|Week of Nov 25 || Mehrshad Sadria || || scGen predicts single-cell perturbation responses || https://www.nature.com/articles/s41592-019-0494-8 ||
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|Week of Nov 30 || Wenjuan Qi || 31|| Network Deconvolution || [https://openreview.net/pdf?id=rkeu30EtvS Paper]  || placeholder||
|Week of Nov 25 || Xuanzhi Huang || ||Comparing Rewinding and Fine-tuning in Neural Network Pruning || https://arxiv.org/abs/2003.02389 || https://youtu.be/2L02BxUaO2Q ||

Latest revision as of 22:29, 1 December 2021

Project Proposal

Paper presentation

Date Name Paper number Title Link to the paper Link to the video
Week of Nov 8 Abhinav Chanana (Example) 1 AUGMIX: A Simple Data Procession method to Improve Robustness And Uncertainity Paper Presentation
Week of Nov 11
Week of Nov 11 Benyamin Jamialahmad Perceiver: General Perception with Iterative Attention [1] [2]
Week of Nov 11
Week of Nov 11
Week of Nov 11
Week of Nov 11
Week of Nov 18 Veronica Salm StructBERT: Incorporating Language Structures Into Pre-Training for Deep Language Understanding Paper Presentation
Week of Nov 18 Youssef Fathi NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis Paper [3]
Week of Nov 18 Wei Liang Deep Stable Learning for Out-Of-Distribution Generalization (Received by CVPR2021) [4] [5]
Week of Nov 18 Taj Jones-McCormick Watch out! Motion is Blurring the Vision of Your Deep Neural Networks https://papers.nips.cc/paper/2020/file/0a73de68f10e15626eb98701ecf03adb-Paper.pdf [6]
Week of Nov 25 Muhammad Maruf Sazed An unsupervised deep learning approach for real-world image denoising https://openreview.net/pdf?id=tIjRAiFmU3y https://drive.google.com/file/d/1BXnuezattSvxOK83FAfiLjKyQc8uKzpq/view?usp=sharing
Week of Nov 25 Yuxiang Huang Reliability Does Matter: An End-to-EndWeakly Supervised Semantic Segmentation Approach Publication Presentation
Week of Nov 25 Yuliang Shi Small-gan: Speeding up gan training using core-sets Paper Presentation
Week of Nov 25 Varnan Sarangian Self-training For Few-shot Transfer Across Extreme Task Differences [7] [8]
Week of Nov 25 Alice Leung ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators Paper Presentation
Week of Nov 25 Maryam Yalsavar Knowledge Extraction with No Observable Data [9] [10]
Week of Nov 25 Shervin Hakimi What Do Neural Networks Learn When Trained With Random Labels? [11]
Week of Nov 25 Islam Nasr Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters [12] [13]
Week of Nov 25 Jared Feng The Autoencoding Variational Autoencoder https://nips.cc/virtual/2020/public/poster_ac10ff1941c540cd87c107330996f4f6.html
Week of Nov 25 Mina Kebriaee Synthesizer: Rethinking Self-Attention for Transformer Models [14] [15]
Week of Nov 25 Mehrshad Sadria scGen predicts single-cell perturbation responses https://www.nature.com/articles/s41592-019-0494-8
Week of Nov 25 Xuanzhi Huang Comparing Rewinding and Fine-tuning in Neural Network Pruning https://arxiv.org/abs/2003.02389 https://youtu.be/2L02BxUaO2Q
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