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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	Summary
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	Summary
Nov 1	Sriram Ganapathi Subramanian	7	Differentiable plasticity: training plastic neural networks with backpropagation	Paper	Summary Slides
Nov 1	Hadi Nekoei	8	Synthesizing Programs for Images using Reinforced Adversarial Learning	Paper	Summary Slides
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 Slides
Nov 6	Ronald Feng	12	Learning to Teach	Paper	Summary Slides
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	Summary
Nov 20	Shubham Koundinya	23	Countering Adversarial Images Using Input Transformations	paper	Summary
Nov 20	Salman Khan	24	Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples	paper	Summary
NOv 22	Soroush Ameli	25	Learning to Navigate in Cities Without a Map	paper	Summary
Nov 22	Ivan Li	26	Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction	Paper	Summary
Nov 22	Sigeng Chen	27	Conditional Neural Processes	Paper	Summary
Nov 27	Aileen Li	28	Unsupervised Neural Machine Translation	Paper	Summary
Nov 27	Xudong Peng	29	Visual Reinforcement Learning with Imagined Goals	Paper	Summary
Nov 27	Xinyue Zhang	30	Policy Optimization with Demonstrations	Paper	Summary
NOv 29	Junyi Zhang	31	Autoregressive Convolutional Neural Networks for Asynchronous Time Series	Paper	Summary
Nov 29	Travis Bender	32	Automatic Goal Generation for Reinforcement Learning Agents	Paper
Nov 29	Patrick Li	33	Dynamic Routing Between Capsules	Paper	Summary
Nov 30	Jiazhen Chen	34	Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning	Paper	Summary
Nov 30	Gaurav Sahu	35	TBD
Nov 23	Kashif Khan	36	Wasserstein Auto-Encoders	Paper	Summary
Nov 23	Shala Chen	37	A Neural Representation of Sketch Drawings	Paper	Summary
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	Summary