Papers
11,015 papers found
Communication Algorithms via Deep Learning
Hyeji Kim, Yihan Jiang, Ranvir B. Rana et al.
Compositional Attention Networks for Machine Reasoning
Drew A. Hudson, Christopher D. Manning
Compositional Obverter Communication Learning from Raw Visual Input
Edward Choi, Angeliki Lazaridou, Nando de Freitas
Compressing Word Embeddings via Deep Compositional Code Learning
Raphael Shu, Hideki Nakayama
Consequentialist conditional cooperation in social dilemmas with imperfect information
Alexander Peysakhovich, Adam Lerer
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
Maruan Al-Shedivat, Trapit Bansal, Yura Burda et al.
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields
Thomas Unterthiner, Bernhard Nessler, Calvin Seward et al.
Countering Adversarial Images using Input Transformations
Chuan Guo, Mayank Rana, Moustapha Cisse et al.
Critical Percolation as a Framework to Analyze the Training of Deep Networks
Zohar Ringel, Rodrigo Andrade de Bem
Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties
Yi Zhou, Yingbin Liang
DCN+: Mixed Objective And Deep Residual Coattention for Question Answering
Caiming Xiong, Victor Zhong, Richard Socher
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Wieland Brendel *, Jonas Rauber *, Matthias Bethge
Decision Boundary Analysis of Adversarial Examples
Warren He, Bo Li, Dawn Song
Decoupling the Layers in Residual Networks
Ricky Fok, Aijun An, Zana Rashidi et al.
Deep Active Learning for Named Entity Recognition
Yanyao Shen, Hyokun Yun, Zachary C. Lipton et al.
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
Bo Zong, Qi Song, Martin Renqiang Min et al.
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
Carlos Riquelme, George Tucker, Jasper Snoek
Deep Complex Networks
Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang et al.
Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer et al.
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski, Stephan Günnemann
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training
Yujun Lin, Song Han, Huizi Mao et al.
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design
Yoav Levine, David Yakira, Nadav Cohen et al.
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem
Abram L. Friesen, Pedro Domingos
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari