microsoft / bayesianizeLinks
Bayesianize: A Bayesian neural network wrapper in pytorch
☆92Updated last year
Alternatives and similar repositories for bayesianize
Users that are interested in bayesianize are comparing it to the libraries listed below
Sorting:
- A library for uncertainty quantification based on PyTorch☆121Updated 4 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆88Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code for the paper "Bayesian Neural Network Priors Revisited"☆60Updated 4 years ago
- ☆252Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 3 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆43Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 8 months ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆37Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Last-layer Laplace approximation code examples☆83Updated 4 years ago
- ☆54Updated last year
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆148Updated 2 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- ☆100Updated 4 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆122Updated 4 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …☆66Updated 5 years ago
- ☆37Updated 3 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 5 years ago
- Official code for the Stochastic Polyak step-size optimizer☆139Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- Reusable BatchBALD implementation☆78Updated last year