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||https://papers.nips.cc/paper/2020/file/0a73de68f10e15626eb98701ecf03adb-Paper.pdf ||[https://www.youtube.com/watch?v=Asv1lMiHCw8] | ||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 || | |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 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] || | |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] | |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 25 || Mehrshad Sadria || || scGen predicts single-cell perturbation responses || https://www.nature.com/articles/s41592-019-0494-8 || | |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 25 || Xuanzhi Huang || || || | |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 |