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m (Record your contributions here [https://docs.google.com/spreadsheets/d/1SxkjNfhOg_eXWpUnVHuIP93E6tEiXEdpm68dQGencgE/edit?usp=sharing])
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|Nov 29 ||Patrick Li  || 33 || Matrix Capsules with EM Routing || [https://openreview.net/pdf?id=HJWLfGWRb Paper]  ||
|Nov 29 ||Patrick Li  || 33 || Matrix Capsules with EM Routing || [https://openreview.net/pdf?id=HJWLfGWRb Paper]  ||
|Makeup || Jiazhen Chen  || 34 || ||  ||  
|Nov 30 || Jiazhen Chen  || 34 || Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning ||  ||  
|Nov 30 || Gaurav Sahu  || 35 || TBD ||  ||
|Nov 30 || Gaurav Sahu  || 35 || TBD ||  ||

Revision as of 13:15, 15 November 2018

Project Proposal

Paper presentation

Your feedback on presentations

Record your contributions here [1]

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).

Date Name Paper number Title Link to the paper Link to the summary
Feb 15 (example) Ri Wang Sequence to sequence learning with neural networks. Paper [Summary]
Oct 25 Dhruv Kumar 1 Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs Paper

Summary Slides

Oct 25 Amirpasha Ghabussi 2 DCN+: Mixed Objective And Deep Residual Coattention for Question Answering Paper


Oct 25 Juan Carrillo 3 Hierarchical Representations for Efficient Architecture Search Paper

Summary Slides

Oct 30 Manpreet Singh Minhas 4 End-to-end Active Object Tracking via Reinforcement Learning Paper Summary
Oct 30 Marvin Pafla 5 Fairness Without Demographics in Repeated Loss Minimization Paper Summary
Oct 30 Glen Chalatov 6 Pixels to Graphs by Associative Embedding Paper


Nov 1 Sriram Ganapathi Subramanian 7 Differentiable plasticity: training plastic neural networks with backpropagation Paper Summary


Nov 1 Hadi Nekoei 8 Synthesizing Programs for Images using Reinforced Adversarial Learning Paper Summary


Nov 1 Henry Chen 9 DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks Paper

Summary Slides

Nov 6 Nargess Heydari 10 Wavelet Pooling For Convolutional Neural Networks Networks Paper Summary Slides
Nov 6 Aravind Ravi 11 Towards Image Understanding from Deep Compression Without Decoding Paper Summary


Nov 6 Ronald Feng 12 Learning to Teach Paper Summary


Nov 8 Neel Bhatt 13 Annotating Object Instances with a Polygon-RNN Paper Summary Slides
Nov 8 Jacob Manuel 14 Co-teaching: Robust Training Deep Neural Networks with Extremely Noisy Labels Paper Summary Slides
Nov 8 Charupriya Sharma 15 A Bayesian Perspective on Generalization and Stochastic Gradient Descent Paper Summary
NOv 13 Sagar Rajendran 16 Zero-Shot Visual Imitation Paper Summary
Nov 13 Ruijie Zhang 17 Searching for Efficient Multi-Scale Architectures for Dense Image Prediction Paper Summary
Nov 13 Neil Budnarain 18 Predicting Floor Level For 911 Calls with Neural Networks and Smartphone Sensor Data Paper Summary
NOv 15 Zheng Ma 19 Reinforcement Learning of Theorem Proving Paper Summary Slides
Nov 15 Abdul Khader Naik 20 Multi-View Data Generation Without View Supervision Paper Summary
Nov 15 Johra Muhammad Moosa 21 Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin Paper Summary Slides
NOv 20 Zahra Rezapour Siahgourabi 22 Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias Paper


Nov 20 Shubham Koundinya 23 Countering Adversarial Images Using Input Transformations paper


Nov 20 Salman Khan 24 Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples paper
NOv 22 Soroush Ameli 25 Learning to Navigate in Cities Without a Map paper
Nov 22 Ivan Li 26 Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction Paper Summary
Nov 22 Sigeng Chen 27 GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models Paper
Nov 27 Aileen Li 28 Spatially Transformed Adversarial Examples Paper
Nov 27 Xudong Peng 29 Visual Reinforcement Learning with Imagined Goals Paper Unfinished
Nov 27 Xinyue Zhang 30 An Inference-Based Policy Gradient Method for Learning Options Paper
NOv 29 Junyi Zhang 31 Autoregressive Convolutional Neural Networks for Asynchronous Time Series Paper
Nov 29 Travis Bender 32 Automatic Goal Generation for Reinforcement Learning Agents Paper
Nov 29 Patrick Li 33 Matrix Capsules with EM Routing Paper
Nov 30 Jiazhen Chen 34 Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Nov 30 Gaurav Sahu 35 TBD
Nov 23 Kashif Khan 36 Wasserstein Auto-Encoders Paper
Nov 30 Ki Beom Lee 38 Detecting Statistical Interactions from Neural Network Weights Paper
Nov 23 Wesley Fisher 39 Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling Paper Summary
Nov 30 Ahmed Afify 40 Don't Decay the Learning Rate, Increase the Batch Size Paper