Papers
11,951 papers found
Can Neural Networks Understand Logical Entailment?
Richard Evans, David Saxton, David Amos et al.
Can recurrent neural networks warp time?
Corentin Tallec, Yann Ollivier
Cascade Adversarial Machine Learning Regularized with a Unified Embedding
Taesik Na, Jong Hwan Ko, Saibal Mukhopadhyay
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis et al.
Certified Defenses against Adversarial Examples
Aditi Raghunathan, Jacob Steinhardt, Percy Liang
Certifying Some Distributional Robustness with Principled Adversarial Training
Aman Sinha, Hongseok Namkoong, John Duchi
cGANs with Projection Discriminator
Takeru Miyato, Masanori Koyama
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Xingjun Ma, Bo Li, Yisen Wang et al.
Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs
Forough Arabshahi, Sameer Singh, Animashree Anandkumar
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
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.