zihangdai / cegan_iclr2017
Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"
☆23Updated 7 years ago
Alternatives and similar repositories for cegan_iclr2017:
Users that are interested in cegan_iclr2017 are comparing it to the libraries listed below
- Implementation of "Variational Inference for Monte Carlo Objectives"☆21Updated 4 years ago
- Implementation of REBAR in PyTorch☆17Updated 6 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 6 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- Professor Forcing, NIPS'16☆46Updated 7 years ago
- ☆17Updated 7 years ago
- Translating neuralese☆44Updated 7 years ago
- Implementation of auxiliary deep generative models for semi-supervised learning☆28Updated 9 years ago
- Learning RNN Hierarchies☆44Updated 8 years ago
- ☆11Updated 8 years ago
- Playground for reinforcement learning algorithms implemented in TensorFlow☆16Updated 8 years ago
- boundary-seeking generative adversarial networks☆46Updated 7 years ago
- A PyTorch implementation of Recurrent Additive Networks by Lee et al. (2017)☆29Updated 7 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- ☆56Updated 6 years ago
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- ☆12Updated 7 years ago
- PixelVAE with or without regularization☆66Updated 7 years ago
- Code for the paper "Representation Learning for Grounded Spatial Reasoning"☆52Updated 4 years ago
- A generic Monte Carlo method based on the Gumbel-Max trick.☆32Updated 8 years ago
- Official implementation for the paper: "Shallow Updates for Deep Reinforcement Learning"☆18Updated 7 years ago
- Deterministic Policy Gradient using torch7☆43Updated 8 years ago
- Weight initialization schemes for PyTorch nn.Modules