
-
Policy Gradient Search: Online Planning and Expert Iteration without Search Trees
Monte Carlo Tree Search (MCTS) algorithms perform simulation-based searc...
04/07/2019 ∙ by Thomas Anthony, et al. ∙4 ∙
share
read it
-
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
We explore the use of Evolution Strategies (ES), a class of black box op...
03/10/2017 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
PixelCNNs are a recently proposed class of powerful generative models wi...
01/19/2017 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Variational Lossy Autoencoder
Representation learning seeks to expose certain aspects of observed data...
11/08/2016 ∙ by Xi Chen, et al. ∙0 ∙
share
read it
-
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
We present weight normalization: a reparameterization of the weight vect...
02/25/2016 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Improving Variational Inference with Inverse Autoregressive Flow
The framework of normalizing flows provides a general strategy for flexi...
06/15/2016 ∙ by Diederik P. Kingma, et al. ∙0 ∙
share
read it
-
A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features
In this note we present a generative model of natural images consisting ...
02/28/2016 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Variational Dropout and the Local Reparameterization Trick
We investigate a local reparameterizaton technique for greatly reducing ...
06/08/2015 ∙ by Diederik P. Kingma, et al. ∙0 ∙
share
read it
-
Improved Techniques for Training GANs
We present a variety of new architectural features and training procedur...
06/10/2016 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap
Recent advances in stochastic gradient variational inference have made i...
10/23/2014 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
We propose a general algorithm for approximating nonstandard Bayesian po...
06/28/2012 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Improving GANs Using Optimal Transport
We present Optimal Transport GAN (OT-GAN), a variant of generative adver...
03/15/2018 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it
-
Learning Montezuma's Revenge from a Single Demonstration
We propose a new method for learning from a single demonstration to solv...
12/08/2018 ∙ by Tim Salimans, et al. ∙0 ∙
share
read it