Alternatives and similar repositories for bayesianize

Users that are interested in bayesianize are comparing it to the libraries listed below

• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆122Updated 3 years ago
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆83Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆44Updated 5 months ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆87Updated last year
• izmailovpavel / understandingbdl
  ☆250Updated 2 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• google-deepmind / conformal_training
  This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…
  ☆129Updated 3 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆96Updated 3 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• p-lambda / verified_calibration
  Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…
  ☆151Updated 3 years ago
• g-benton / loss-surface-simplexes
  ☆100Updated 3 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆78Updated 2 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• Sanaelotfi / Bayesian_model_comparison
  Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
  ☆37Updated 3 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆93Updated 5 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆43Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆114Updated 3 years ago
• cybertronai / pytorch-sso
  PyTorch-SSO: Scalable Second-Order methods in PyTorch
  ☆147Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• BlackHC / batchbald_redux
  Reusable BatchBALD implementation
  ☆79Updated last year
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• ayulockin / LossLandscape
  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
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆273Updated 3 years ago
• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆244Updated 5 years ago
• JanRocketMan / regression-prior-networks
  An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.
  ☆36Updated 4 years ago
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆70Updated last year
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆78Updated last year