Papers
Lifelong Learning with Dynamically Expandable Networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee et al.
The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings
Tomer Galanti, Lior Wolf, Sagie Benaim
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris, Praveer Singh, Nikos Komodakis
Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova et al.
Deep Sensing: Active Sensing using Multi-directional Recurrent Neural Networks
Jinsung Yoon, William R. Zame, Mihaela van der Schaar
Model-Ensemble Trust-Region Policy Optimization
Thanard Kurutach, Ignasi Clavera, Yan Duan et al.
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie Chen, Tengfei Ma, Cao Xiao
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang, Yixuan Li, R. Srikant
Distributed Prioritized Experience Replay
Dan Horgan, John Quan, David Budden et al.
Skip Connections Eliminate Singularities
Emin Orhan, Xaq Pitkow
Eigenoption Discovery through the Deep Successor Representation
Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo et al.
Training and Inference with Integers in Deep Neural Networks
Shuang Wu, Guoqi Li, Feng Chen et al.
Parametrized Hierarchical Procedures for Neural Programming
Roy Fox, Richard Shin, Sanjay Krishnan et al.
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski, Stephan Günnemann
Unsupervised Neural Machine Translation
Mikel Artetxe, Gorka Labaka, Eneko Agirre et al.
Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect
Xiang Wei, Boqing Gong, Zixia Liu et al.
Learning to Represent Programs with Graphs
Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi
On Unifying Deep Generative Models
Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov et al.
Routing Networks: Adaptive Selection of Non-Linear Functions for Multi-Task Learning
Clemens Rosenbaum, Tim Klinger, Matthew Riemer
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama et al.
Improving GANs Using Optimal Transport
Tim Salimans, Han Zhang, Alec Radford et al.
Understanding Deep Neural Networks with Rectified Linear Units
Raman Arora, Amitabh Basu, Poorya Mianjy et al.
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
Sandeep Subramanian, Adam Trischler, Yoshua Bengio et al.
Fidelity-Weighted Learning
Mostafa Dehghani, Arash Mehrjou, Stephan Gouws et al.
Initialization matters: Orthogonal Predictive State Recurrent Neural Networks
Krzysztof Choromanski, Carlton Downey, Byron Boots