Marlan McInnes-Taylor's schedule

When Paper What
Sun Sep 05 Exact solutions to the nonlinear dynamics of learning in deep linear neural networks , Saxe, McClelland, Ganguli; 2013 Coding
Fri Sep 10 Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates , Smith, Topin; 2017 Review both summaries
Wed Sep 15 Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks , Salimans, Kingma; 2016 Draft Summary
Sun Sep 19 Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks , Salimans, Kingma; 2016 Final Summary
Wed Sep 22 End-To-End Memory Networks , Sukhbaatar, Szlam, Weston, Fergus; 2015 Draft Summary
Sun Sep 26 End-To-End Memory Networks , Sukhbaatar, Szlam, Weston, Fergus; 2015 Final Summary
Sun Oct 03 Reformer: The Efficient Transformer , Kitaev, Kaiser, Levskaya; 2020 Coding
Fri Oct 08 Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions , Wang, Xie, Li, Fan, Song, Liang, Lu, Luo, Shao; 2021 Review both summaries
Wed Oct 13 Implicit Geometric Regularization for Learning Shapes , Gropp, Yariv, Haim, Atzmon, Lipman; 2020 Draft Summary
Sun Oct 17 Implicit Geometric Regularization for Learning Shapes , Gropp, Yariv, Haim, Atzmon, Lipman; 2020 Final Summary
Wed Oct 20 Cascade R-CNN: Delving into High Quality Object Detection , Cai, Vasconcelos; 2017 Draft Summary
Sun Oct 24 Cascade R-CNN: Delving into High Quality Object Detection , Cai, Vasconcelos; 2017 Final Summary
Sun Oct 31 PointCNN: Convolution On $\mathcal{X}$-Transformed Points , Li, Bu, Sun, Wu, Di, Chen; 2018 Coding
Fri Nov 05 Learning Transferable Visual Models From Natural Language Supervision , Radford, Kim, Hallacy, Ramesh, Goh, Agarwal, Sastry, Askell, Mishkin, Clark, Krueger, Sutskever; 2021 Review both summaries