Jay Whang's schedule

When Paper What
Fri Sep 03 Maxout Networks , Goodfellow, Warde-Farley, Mirza, Courville, Bengio; 2013 Review both summaries
Sun Sep 12 Adam: A Method for Stochastic Optimization , Kingma, Ba; 2014 Coding
Wed Sep 15 Layer Normalization , Ba, Kiros, Hinton; 2016 Draft Summary
Sun Sep 19 Layer Normalization , Ba, Kiros, Hinton; 2016 Final Summary
Wed Sep 22 Language Models are Few-Shot Learners , Brown, Mann, Ryder, Subbiah, Kaplan, Dhariwal, Neelakantan, Shyam, Sastry, Askell, Agarwal, Herbert-Voss, Krueger, Henighan, Child, Ramesh, Ziegler, Wu, Winter, Hesse, Chen, Sigler, Litwin, Gray, Chess, Clark, Berner, McCandlish, Radford, Sutskever, Amodei; 2020 Draft Summary
Sun Sep 26 Language Models are Few-Shot Learners , Brown, Mann, Ryder, Subbiah, Kaplan, Dhariwal, Neelakantan, Shyam, Sastry, Askell, Agarwal, Herbert-Voss, Krueger, Henighan, Child, Ramesh, Ziegler, Wu, Winter, Hesse, Chen, Sigler, Litwin, Gray, Chess, Clark, Berner, McCandlish, Radford, Sutskever, Amodei; 2020 Final Summary
Fri Oct 01 Compressive Transformers for Long-Range Sequence Modelling , Rae, Potapenko, Jayakumar, Lillicrap; 2019 Review both summaries
Sun Oct 10 Perceiver: General Perception with Iterative Attention , Jaegle, Gimeno, Brock, Zisserman, Vinyals, Carreira; 2021 Coding
Wed Oct 13 Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains , Tancik, Srinivasan, Mildenhall, Fridovich-Keil, Raghavan, Singhal, Ramamoorthi, Barron, Ng; 2020 Draft Summary
Sun Oct 17 Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains , Tancik, Srinivasan, Mildenhall, Fridovich-Keil, Raghavan, Singhal, Ramamoorthi, Barron, Ng; 2020 Final Summary
Wed Oct 20 Deformable DETR: Deformable Transformers for End-to-End Object Detection , Zhu, Su, Lu, Li, Wang, Dai; 2020 Draft Summary
Sun Oct 24 Deformable DETR: Deformable Transformers for End-to-End Object Detection , Zhu, Su, Lu, Li, Wang, Dai; 2020 Final Summary
Fri Oct 29 Dynamic Graph CNN for Learning on Point Clouds , Wang, Sun, Liu, Sarma, Bronstein, Solomon; 2018 Review both summaries
Sun Nov 07 Class-Balanced Loss Based on Effective Number of Samples , Cui, Jia, Lin, Song, Belongie; 2019 Coding