Papers
11,015 papers found
Kronecker-factored Curvature Approximations for Recurrent Neural Networks
James Martens, Jimmy Ba, Matt Johnson
Large scale distributed neural network training through online distillation
Rohan Anil, Gabriel Pereyra, Alexandre Passos et al.
Large Scale Optimal Transport and Mapping Estimation
Vivien Seguy, Bharath Bhushan Damodaran, Remi Flamary et al.
Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models
Jesse Engel, Matthew Hoffman, Adam Roberts
Latent Space Oddity: on the Curvature of Deep Generative Models
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
Learning a Generative Model for Validity in Complex Discrete Structures
Dave Janz, Jos van der Westhuizen, Brooks Paige et al.
Learning an Embedding Space for Transferable Robot Skills
Karol Hausman, Jost Tobias Springenberg, Ziyu Wang et al.
Learning a neural response metric for retinal prosthesis
Nishal P Shah, Sasidhar Madugula, EJ Chichilnisky et al.
Learning Approximate Inference Networks for Structured Prediction
Lifu Tu, Kevin Gimpel
Learning Awareness Models
Brandon Amos, Laurent Dinh, Serkan Cabi et al.
Learning Deep Mean Field Games for Modeling Large Population Behavior
Jiachen Yang, Xiaojing Ye, Rakshit Trivedi et al.
Learning Differentially Private Recurrent Language Models
H. Brendan McMahan, Daniel Ramage, Kunal Talwar et al.
Learning Discrete Weights Using the Local Reparameterization Trick
Oran Shayer, Dan Levi, Ethan Fetaya
Learning from Between-class Examples for Deep Sound Recognition
Yuji Tokozume, Yoshitaka Ushiku, Tatsuya Harada
Learning From Noisy Singly-labeled Data
Ashish Khetan, Zachary C. Lipton, Animashree Anandkumar
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
Sandeep Subramanian, Adam Trischler, Yoshua Bengio et al.
Learning how to explain neural networks: PatternNet and PatternAttribution
Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber et al.
Learning Intrinsic Sparse Structures within Long Short-Term Memory
Wei Wen, Yuxiong He, Samyam Rajbhandari et al.
Learning Latent Permutations with Gumbel-Sinkhorn Networks
Gonzalo Mena, David Belanger, Scott Linderman et al.
Learning One-hidden-layer Neural Networks with Landscape Design
Rong Ge, Jason D. Lee, Tengyu Ma
Learning Parametric Closed-Loop Policies for Markov Potential Games
Sergio Valcarcel Macua, Javier Zazo, Santiago Zazo
Learning Robust Rewards with Adverserial Inverse Reinforcement Learning
Justin Fu, Katie Luo, Sergey Levine
Learning Sparse Latent Representations with the Deep Copula Information Bottleneck
Aleksander Wieczorek*, Mario Wieser*, Damian Murezzan et al.
Learning Sparse Neural Networks through L_0 Regularization
Christos Louizos, Max Welling, Diederik P. Kingma