Papers
Deep Layers as Stochastic Solvers
Adel Bibi, Bernard Ghanem, Vladlen Koltun et al.
Graph HyperNetworks for Neural Architecture Search
Chris Zhang, Mengye Ren, Raquel Urtasun
Learning Self-Imitating Diverse Policies
Tanmay Gangwani, Qiang Liu, Jian Peng
Slimmable Neural Networks
Jiahui Yu, Linjie Yang, Ning Xu et al.
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou et al.
Complement Objective Training
Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu et al.
ProMP: Proximal Meta-Policy Search
Jonas Rothfuss, Dennis Lee, Ignasi Clavera et al.
Learning Multi-Level Hierarchies with Hindsight
Andrew Levy, George Konidaris, Robert Platt et al.
Discovery of Natural Language Concepts in Individual Units of CNNs
Seil Na, Yo Joong Choe, Dong-Hyun Lee et al.
Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity
Thomas Miconi, Aditya Rawal, Jeff Clune et al.
A2BCD: Asynchronous Acceleration with Optimal Complexity
Robert Hannah, Fei Feng, Wotao Yin
An Empirical study of Binary Neural Networks' Optimisation
Milad Alizadeh, Javier Fernández-Marqués, Nicholas D. Lane et al.
Universal Transformers
Mostafa Dehghani, Stephan Gouws, Oriol Vinyals et al.
LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING
Yanbin Liu, Juho Lee, Minseop Park et al.
Improving Sequence-to-Sequence Learning via Optimal Transport
Liqun Chen, Yizhe Zhang, Ruiyi Zhang et al.
Verification of Non-Linear Specifications for Neural Networks
Chongli Qin, Krishnamurthy (Dj) Dvijotham, Brendan O'Donoghue et al.
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset
Curtis Hawthorne, Andriy Stasyuk, Adam Roberts et al.
Variational Autoencoders with Jointly Optimized Latent Dependency Structure
Jiawei He, Yu Gong, Joseph Marino et al.
A comprehensive, application-oriented study of catastrophic forgetting in DNNs
B. Pfülb, A. Gepperth
Efficient Training on Very Large Corpora via Gramian Estimation
Walid Krichene, Nicolas Mayoraz, Steffen Rendle et al.
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
Roman Novak, Lechao Xiao, Yasaman Bahri et al.
Unsupervised Domain Adaptation for Distance Metric Learning
Kihyuk Sohn, Wenling Shang, Xiang Yu et al.
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis et al.
Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Ying Wen, Yaodong Yang, Rui Luo et al.
Decoupled Weight Decay Regularization
Ilya Loshchilov, Frank Hutter