Papers
Multi-Scale Dense Networks for Resource Efficient Image Classification
Gao Huang, Danlu Chen, Tianhong Li et al.
Emergent Communication through Negotiation
Kris Cao, Angeliki Lazaridou, Marc Lanctot et al.
TRAINING GENERATIVE ADVERSARIAL NETWORKS VIA PRIMAL-DUAL SUBGRADIENT METHODS: A LAGRANGIAN PERSPECTIVE ON GAN
Xu Chen, Jiang Wang, Hao Ge
Cascade Adversarial Machine Learning Regularized with a Unified Embedding
Taesik Na, Jong Hwan Ko, Saibal Mukhopadhyay
VoiceLoop: Voice Fitting and Synthesis via a Phonological Loop
Yaniv Taigman, Lior Wolf, Adam Polyak et al.
Modular Continual Learning in a Unified Visual Environment
Kevin T. Feigelis, Blue Sheffer, Daniel L. K. Yamins
Synthetic and Natural Noise Both Break Neural Machine Translation
Yonatan Belinkov, Yonatan Bisk
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras, Timo Aila, Samuli Laine et al.
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
Will Grathwohl, Dami Choi, Yuhuai Wu et al.
Divide and Conquer Networks
Alex Nowak, David Folqué, Joan Bruna
Alternating Multi-bit Quantization for Recurrent Neural Networks
Chen Xu, Jianqiang Yao, Zhouchen Lin et al.
Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander G. de G. Matthews, Jiri Hron, Mark Rowland et al.
N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning
Anubhav Ashok, Nicholas Rhinehart, Fares Beainy et al.
Divide-and-Conquer Reinforcement Learning
Dibya Ghosh, Avi Singh, Aravind Rajeswaran et al.
Hierarchical Representations for Efficient Architecture Search
Hanxiao Liu, Karen Simonyan, Oriol Vinyals et al.
Learning from Between-class Examples for Deep Sound Recognition
Yuji Tokozume, Yoshitaka Ushiku, Tatsuya Harada
Learning to Teach
Yang Fan, Fei Tian, Tao Qin et al.
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt et al.
Espresso: Efficient Forward Propagation for Binary Deep Neural Networks
Fabrizio Pedersoli, George Tzanetakis, Andrea Tagliasacchi
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis et al.
Simulating Action Dynamics with Neural Process Networks
Antoine Bosselut, Omer Levy, Ari Holtzman et al.
Sensitivity and Generalization in Neural Networks: an Empirical Study
Roman Novak, Yasaman Bahri, Daniel A. Abolafia et al.
On the State of the Art of Evaluation in Neural Language Models
Gábor Melis, Chris Dyer, Phil Blunsom
Thermometer Encoding: One Hot Way To Resist Adversarial Examples
Jacob Buckman, Aurko Roy, Colin Raffel et al.