Papers
Improving Generalization and Stability of Generative Adversarial Networks
Hoang Thanh-Tung, Truyen Tran, Svetha Venkatesh
The Singular Values of Convolutional Layers
Hanie Sedghi, Vineet Gupta, Philip M. Long
ACCELERATING NONCONVEX LEARNING VIA REPLICA EXCHANGE LANGEVIN DIFFUSION
Yi Chen, Jinglin Chen, Jing Dong et al.
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Daniel McDuff, Ashish Kapoor
Small nonlinearities in activation functions create bad local minima in neural networks
Chulhee Yun, Suvrit Sra, Ali Jadbabaie
ADef: an Iterative Algorithm to Construct Adversarial Deformations
Rima Alaifari, Giovanni S. Alberti, Tandri Gauksson
code2seq: Generating Sequences from Structured Representations of Code
Uri Alon, Shaked Brody, Omer Levy et al.
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications
Carson Eisenach, Haichuan Yang, Ji Liu et al.
Relaxed Quantization for Discretized Neural Networks
Christos Louizos, Matthias Reisser, Tijmen Blankevoort et al.
Sparse Dictionary Learning by Dynamical Neural Networks
Tsung-Han Lin, Ping Tak Peter Tang
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
Jan Svoboda, Jonathan Masci, Federico Monti et al.
Whitening and Coloring Batch Transform for GANs
Aliaksandr Siarohin, Enver Sangineto, Nicu Sebe
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data
Jianbo Chen, Le Song, Martin J. Wainwright et al.
Deep reinforcement learning with relational inductive biases
Vinicius Zambaldi, David Raposo, Adam Santoro et al.
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks, Thomas Dietterich
GO Gradient for Expectation-Based Objectives
Yulai Cong, Miaoyun Zhao, Ke Bai et al.
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees
James Jordon, Jinsung Yoon, Mihaela van der Schaar
Auxiliary Variational MCMC
Raza Habib, David Barber
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks
James Jordon, Jinsung Yoon, Mihaela van der Schaar
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
Nan Lu, Gang Niu, Aditya Krishna Menon et al.
Approximability of Discriminators Implies Diversity in GANs
Yu Bai, Tengyu Ma, Andrej Risteski
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Yonatan Geifman, Guy Uziel, Ran El-Yaniv
SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY
Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton et al.