chenxy99 / Stein-Variational-Gradient-Descent
SVGD implementation
☆10Updated 6 years ago
Alternatives and similar repositories for Stein-Variational-Gradient-Descent:
Users that are interested in Stein-Variational-Gradient-Descent are comparing it to the libraries listed below
- PyTorch implementation of Stein Variational Gradient Descent☆43Updated last year
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated last year
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 6 months ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- ☆10Updated 7 years ago
- Code release for the ICLR paper☆20Updated 6 years ago
- A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN☆18Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆83Updated 4 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆17Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Tensorflow implementation of Stein Variational Gradient Descent (SVGD)☆25Updated 7 years ago
- code for Stein Neural Sampler☆22Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- ☆23Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- This is the official source code for Sequential Neural Processes.☆40Updated 2 years ago
- Library for Auto-Encoding Sequential Monte Carlo☆18Updated last year
- A PyTorch Implementation of the Importance Weighted Autoencoders☆40Updated 6 years ago
- ☆30Updated 4 years ago
- ☆38Updated 4 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Learning generative models with Sinkhorn Loss☆28Updated 6 years ago
- Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning☆28Updated 3 years ago
- ☆28Updated 3 years ago