Alternatives and similar repositories for vbll:

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

• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated last year
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆28Updated last month
• bmucsanyi / untangle
  Large-scale uncertainty benchmark in deep learning.
  ☆53Updated last month
• konstantinos-p / Bayesian-Neural-Networks-Reading-List
  A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…
  ☆52Updated last year
• google-deepmind / conformal_training
  This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…
  ☆129Updated 2 years ago
• chenw20 / SGPA
  Example code of Sparse Gaussian Process Attention (ICLR 2023)
  ☆24Updated 8 months ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆45Updated 2 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆207Updated 4 months ago
• automl / PFNs
  Our maintained PFN repository. Come here to train SOTA PFNs.
  ☆65Updated last month
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆121Updated 3 years ago
• ratschlab / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆76Updated 7 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆71Updated 2 years ago
• google-research / hyperbo
  Pre-trained Gaussian processes for Bayesian optimization
  ☆90Updated 3 months ago
• automl / PFNs4BO
  The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization
  ☆26Updated last year
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆97Updated 10 months ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated 10 months ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆48Updated 10 months ago
• martius-lab / beta-nll
  beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022
  ☆41Updated 2 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆112Updated last week
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆21Updated 2 years ago
• jongharyu / neural-svd
  ☆16Updated 6 months ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 3 years ago
• Feuermagier / Beyond_Deep_Ensembles
  Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"
  ☆22Updated last year
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 2 years ago
• TyXe-BDL / TyXe
  ☆149Updated 2 years ago