ChunyuanLI / SVGDLinks
Tensorflow implementation of Stein Variational Gradient Descent (SVGD)
☆26Updated 7 years ago
Alternatives and similar repositories for SVGD
Users that are interested in SVGD are comparing it to the libraries listed below
Sorting:
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆45Updated 2 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 9 months ago
- ☆54Updated 11 months ago
- Code release for the ICLR paper☆21Updated 7 years ago
- ☆38Updated 5 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- [ICLR 2022] Path integral sampler☆48Updated last year
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago
- ☆40Updated 6 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 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
- Limitations of the Empirical Fisher Approximation☆47Updated 4 months ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago
- ☆59Updated 6 years ago
- ☆30Updated 4 years ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- ☆63Updated last year
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Normalizing Flows in Jax☆107Updated 4 years ago