Papers
Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Victor Zhong, Caiming Xiong, Nitish Shirish Keskar et al.
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong et al.
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
Tiago Ramalho, Marta Garnelo
On the Turing Completeness of Modern Neural Network Architectures
Jorge Pérez, Javier Marinković, Pablo Barceló
Towards the first adversarially robust neural network model on MNIST
Lukas Schott, Jonas Rauber, Matthias Bethge et al.
Evaluating Robustness of Neural Networks with Mixed Integer Programming
Vincent Tjeng, Kai Y. Xiao, Russ Tedrake
The Unusual Effectiveness of Averaging in GAN Training
Yasin Yaz{\i}c{\i}, Chuan-Sheng Foo, Stefan Winkler et al.
Graph Wavelet Neural Network
Bingbing Xu, Huawei Shen, Qi Cao et al.
Double Viterbi: Weight Encoding for High Compression Ratio and Fast On-Chip Reconstruction for Deep Neural Network
Daehyun Ahn, Dongsoo Lee, Taesu Kim et al.
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy
Yuan Xie, Boyi Liu, Qiang Liu et al.
Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation
Ehsan Hosseini-Asl, Yingbo Zhou, Caiming Xiong et al.
Meta-Learning For Stochastic Gradient MCMC
Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato
Efficient Lifelong Learning with A-GEM
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach et al.
Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models
Eirikur Agustsson, Alexander Sage, Radu Timofte et al.
Learning a SAT Solver from Single-Bit Supervision
Daniel Selsam, Matthew Lamm, Benedikt B\"{u}nz et al.
Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration
Xiaoshuai Zhang, Yiping Lu, Jiaying Liu et al.
Learning Recurrent Binary/Ternary Weights
Arash Ardakani, Zhengyun Ji, Sean C. Smithson et al.
Generative Code Modeling with Graphs
Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt et al.
Trellis Networks for Sequence Modeling
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
Meta-Learning Probabilistic Inference for Prediction
Jonathan Gordon, John Bronskill, Matthias Bauer et al.
Critical Learning Periods in Deep Networks
Alessandro Achille, Matteo Rovere, Stefano Soatto
Attention, Learn to Solve Routing Problems!
Wouter Kool, Herke van Hoof, Max Welling
Learning to Make Analogies by Contrasting Abstract Relational Structure
Felix Hill, Adam Santoro, David Barrett et al.
Towards Understanding Regularization in Batch Normalization
Ping Luo, Xinjiang Wang, Wenqi Shao et al.
GamePad: A Learning Environment for Theorem Proving
Daniel Huang, Prafulla Dhariwal, Dawn Song et al.