Papers
Neural Speed Reading with Structural-Jump-LSTM
Christian Hansen, Casper Hansen, Stephen Alstrup et al.
Information Theoretic lower bounds on negative log likelihood
Luis A. Lastras-Montaño
Equi-normalization of Neural Networks
Pierre Stock, Benjamin Graham, Rémi Gribonval et al.
LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators
Jianan Li, Jimei Yang, Aaron Hertzmann et al.
SGD Converges to Global Minimum in Deep Learning via Star-convex Path
Yi Zhou, Junjie Yang, Huishuai Zhang et al.
Learning from Positive and Unlabeled Data with a Selection Bias
Masahiro Kato, Takeshi Teshima, Junya Honda
Multi-Domain Adversarial Learning
Alice Schoenauer-Sebag, Louise Heinrich, Marc Schoenauer et al.
Overcoming Catastrophic Forgetting for Continual Learning via Model Adaptation
Wenpeng Hu, Zhou Lin, Bing Liu et al.
Minimum Divergence vs. Maximum Margin: an Empirical Comparison on Seq2Seq Models
Huan Zhang, Hai Zhao
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Daewoo Kim, Sangwoo Moon, David Hostallero et al.
Aggregated Momentum: Stability Through Passive Damping
James Lucas, Shengyang Sun, Richard Zemel et al.
Learning Factorized Multimodal Representations
Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh et al.
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
Wenda Zhou, Victor Veitch, Morgane Austern et al.
Riemannian Adaptive Optimization Methods
Gary Becigneul, Octavian-Eugen Ganea
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin, Matthias Hüser, Francesco Locatello et al.
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock, Jeff Donahue, Karen Simonyan
Improving MMD-GAN Training with Repulsive Loss Function
Wei Wang, Yuan Sun, Saman Halgamuge
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos, Patricia Rubisch, Claudio Michaelis et al.
FUNCTIONAL VARIATIONAL BAYESIAN NEURAL NETWORKS
Shengyang Sun, Guodong Zhang, Jiaxin Shi et al.
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikang Shen, Shawn Tan, Alessandro Sordoni et al.
Analysing Mathematical Reasoning Abilities of Neural Models
David Saxton, Edward Grefenstette, Felix Hill et al.
Learning Representations of Sets through Optimized Permutations
Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
Measuring Compositionality in Representation Learning
Jacob Andreas
Detecting Egregious Responses in Neural Sequence-to-sequence Models
Tianxing He, James Glass