Difference between revisions of "stat940F21"

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(Record your contributions here [https://docs.google.com/spreadsheets/d/1Me_O000pNxeTwNGEac57XakecG1wahvwGE5n36DGIlM/edit#gid=0])
(Paper presentation)
 
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== [[F20-STAT 946-Proposal| Project Proposal ]] ==
 
== [[F20-STAT 946-Proposal| Project Proposal ]] ==
  
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=Paper presentation=
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{| class="wikitable"
  
= Record your contributions here [https://docs.google.com/spreadsheets/d/1Me_O000pNxeTwNGEac57XakecG1wahvwGE5n36DGIlM/edit?usp=sharing]=
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{| border="1" cellpadding="3"
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|-
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|width="120pt"|Date
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|width="200pt"|Name
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|width="30pt"|Paper number
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|width="900pt"|Title
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|width="30pt"|Link to the paper
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|width="30pt"|Link to the video
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|-
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|-
  
Use the following notations:
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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 ]
 
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P: You have written a summary/critique on the paper.
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|Week of Nov 11 ||  || ||  ||  ||
 
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T: You had a technical contribution on a paper (excluding the paper that you present).
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|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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E: You had an editorial contribution on a paper (excluding the paper that you present).
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|Week of Nov 11 ||  || ||  ||  ||
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|Week of Nov 11 ||  || ||  ||  ||
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|Week of Nov 11 ||  || ||  ||  ||
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|Week of Nov 11 ||  || ||  ||  ||
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|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 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 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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|-
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|Week of Nov 18 || Taj Jones-McCormick  || ||Watch out! Motion is Blurring the Vision of Your Deep Neural Networks
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||https://papers.nips.cc/paper/2020/file/0a73de68f10e15626eb98701ecf03adb-Paper.pdf ||[https://www.youtube.com/watch?v=Asv1lMiHCw8]
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|-
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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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|-
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|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 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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|-
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|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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|-
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|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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|-
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|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 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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|-
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|Week of Nov 25 || Islam Nasr || || Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters
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|| [http://ceur-ws.org/Vol-2846/paper10.pdf]  || [https://youtu.be/HP9zyxTOioA] ||
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|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 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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|-
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|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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|-
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|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 23:29, 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