trevorcampbell / bayesian-coresets
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
- A community repository for benchmarking Bayesian methods☆109Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆81Updated 7 months ago
- python code for kernel methods☆38Updated 6 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆56Updated 3 years ago
- ☆236Updated 2 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 9 months ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆244Updated 5 years ago
- ☆42Updated 6 years ago
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆144Updated 2 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated 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)☆64Updated 5 years ago
- Functional tensors for probabilistic programming☆237Updated last year
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆81Updated 4 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆98Updated 5 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- ☆148Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆41Updated last year
- Hessian spectral density estimation in TF and Jax☆121Updated 4 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 3 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Convolutional Neural Tangent Kernel☆109Updated 5 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆145Updated last year
- Package implementing various parametric and nonparametric methods for conditional density estimation☆191Updated last year