YingzhenLi / VRbound
code release for the NIPS 2016 paper
☆26Updated 8 years ago
Alternatives and similar repositories for VRbound:
Users that are interested in VRbound are comparing it to the libraries listed below
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 5 months ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated last year
- A tensorflow implementation of VAE training with Renyi divergence☆31Updated 8 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 5 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- ☆37Updated 5 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆83Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated 2 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆52Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Experiments for the Neural Autoregressive Flows paper☆123Updated 3 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for 'Inference Suboptimality in Variational Autoencoders'☆10Updated 4 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- Code release for the ICLR paper☆20Updated 6 years ago