hughsalimbeni / bayesian_benchmarksLinks
A community repository for benchmarking Bayesian methods
☆112Updated 4 years ago
Alternatives and similar repositories for bayesian_benchmarks
Users that are interested in bayesian_benchmarks are comparing it to the libraries listed below
Sorting:
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆101Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆49Updated 5 years ago
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- Automated Scalable Bayesian Inference☆131Updated 3 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆122Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- ☆40Updated 6 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 4 years ago
- Gaussian Processes for Sequential Data☆19Updated 4 years ago
- ☆172Updated last year
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- ☆29Updated 6 years ago
- Library for Deep Gaussian Processes based on GPflow☆18Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆94Updated 4 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- Bayesian neural network package☆152Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- The collection of recent papers about variational inference☆84Updated 6 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago