Papers
11,015 papers found
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
Florian Mai, Lukas Galke, Ansgar Scherp
Characterizing Audio Adversarial Examples Using Temporal Dependency
Zhuolin Yang, Bo Li, Pin-Yu Chen et al.
ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech
Wei Ping, Kainan Peng, Jitong Chen
Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering
Victor Zhong, Caiming Xiong, Nitish Shirish Keskar et al.
code2seq: Generating Sequences from Structured Representations of Code
Uri Alon, Shaked Brody, Omer Levy et al.
Combinatorial Attacks on Binarized Neural Networks
Elias B Khalil, Amrita Gupta, Bistra Dilkina
Competitive experience replay
Hao Liu, Alexander Trott, Richard Socher et al.
Complement Objective Training
Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu et al.
Composing Complex Skills by Learning Transition Policies
Youngwoon Lee*, Shao-Hua Sun*, Sriram Somasundaram et al.
Conditional Network Embeddings
Bo Kang, Jefrey Lijffijt, Tijl De Bie
Context-adaptive Entropy Model for End-to-end Optimized Image Compression
Jooyoung Lee, Seunghyun Cho, Seung-Kwon Beack
Contingency-Aware Exploration in Reinforcement Learning
Jongwook Choi, Yijie Guo, Marcin Moczulski et al.
Convolutional Neural Networks on Non-uniform Geometrical Signals Using Euclidean Spectral Transformation
Chiyu Max Jiang, Dequan Wang, Jingwei Huang et al.
Cost-Sensitive Robustness against Adversarial Examples
Xiao Zhang, David Evans
Critical Learning Periods in Deep Networks
Alessandro Achille, Matteo Rovere, Stefano Soatto
DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, Yiming Yang
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski et al.
Decoupled Weight Decay Regularization
Ilya Loshchilov, Frank Hutter
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks, Mantas Mazeika, Thomas Dietterich
Deep Convolutional Networks as shallow Gaussian Processes
Adrià Garriga-Alonso, Carl Edward Rasmussen, Laurence Aitchison
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
Reinhard Heckel, Paul Hand
Deep Frank-Wolfe For Neural Network Optimization
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton et al.
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
Michael Lutter, Christian Ritter, Jan Peters