trevorcampbell / bayesian-coresetsLinks
Automated Scalable Bayesian Inference
☆131Updated 3 years ago
Alternatives and similar repositories for bayesian-coresets
Users that are interested in bayesian-coresets are comparing it to the libraries listed below
Sorting:
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆39Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 4 years ago
- Python toolbox for sampling Determinantal Point Processes☆230Updated 11 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆241Updated 2 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- ☆169Updated last year
- ☆43Updated 6 years ago
- Deep neural network kernel for Gaussian process☆208Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks☆301Updated last month
- The collection of papers about combining deep learning and Bayesian nonparametrics☆121Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆196Updated 2 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 4 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- ☆59Updated 6 years ago
- python code for kernel methods☆40Updated 6 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- ☆40Updated 6 years ago
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆37Updated 5 years ago