Papers
11,015 papers found
Emergent Complexity via Multi-Agent Competition
Trapit Bansal, Jakub Pachocki, Szymon Sidor et al.
Emergent Translation in Multi-Agent Communication
Jason Lee, Kyunghyun Cho, Jason Weston et al.
Empirical Risk Landscape Analysis for Understanding Deep Neural Networks
Pan Zhou, Jiashi Feng
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang, Yixuan Li, R. Srikant
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot et al.
Espresso: Efficient Forward Propagation for Binary Deep Neural Networks
Fabrizio Pedersoli, George Tzanetakis, Andrea Tagliasacchi
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Tsui-Wei Weng*, Huan Zhang*, Pin-Yu Chen et al.
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
Shuohang Wang, Mo Yu, Jing Jiang et al.
Expressive power of recurrent neural networks
Valentin Khrulkov, Alexander Novikov, Ivan Oseledets
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie Chen, Tengfei Ma, Cao Xiao
FearNet: Brain-Inspired Model for Incremental Learning
Ronald Kemker, Christopher Kanan
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions
Scott Reed, Yutian Chen, Thomas Paine et al.
Few-Shot Learning with Graph Neural Networks
Victor Garcia Satorras, Joan Bruna Estrach
Fidelity-Weighted Learning
Mostafa Dehghani, Arash Mehrjou, Stephan Gouws et al.
Fix your classifier: the marginal value of training the last weight layer
Elad Hoffer, Itay Hubara, Daniel Soudry
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
Yeming Wen, Paul Vicol, Jimmy Ba et al.
Fraternal Dropout
Konrad Zolna, Devansh Arpit, Dendi Suhubdy et al.
FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension
Hsin-Yuan Huang, Chenguang Zhu, Yelong Shen et al.
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets
Jinsung Yoon, James Jordon, Mihaela van der Schaar
Gaussian Process Behaviour in Wide Deep Neural Networks
Alexander G. de G. Matthews, Jiri Hron, Mark Rowland et al.
Generalizing Across Domains via Cross-Gradient Training
Shiv Shankar*, Vihari Piratla*, Soumen Chakrabarti et al.
Generalizing Hamiltonian Monte Carlo with Neural Networks
Daniel Levy, Matt D. Hoffman, Jascha Sohl-Dickstein
Generating Natural Adversarial Examples
Zhengli Zhao, Dheeru Dua, Sameer Singh
Generating Wikipedia by Summarizing Long Sequences
Peter J. Liu*, Mohammad Saleh*, Etienne Pot et al.
Generative Models of Visually Grounded Imagination
Ramakrishna Vedantam, Ian Fischer, Jonathan Huang et al.