Alternatives and similar repositories for 2023-ProbAI

Users that are interested in 2023-ProbAI are comparing it to the libraries listed below

• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆91Updated 2 years ago
• TyXe-BDL / TyXe
  ☆156Updated 3 years ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆181Updated 3 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆45Updated last year
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆52Updated 6 months ago
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆16Updated 3 years ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆36Updated 5 months ago
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆20Updated 3 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆228Updated last year
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 3 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆44Updated 8 months ago
• juangamella / causal-chamber
  Public dataset repository for the Causal Chamber Project
  ☆58Updated 3 months ago
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆12Updated 2 years ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆14Updated 2 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆79Updated 4 months ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆252Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆60Updated 4 years ago
• psanch21 / causal-flows
  ☆53Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• team-approx-bayes / ivon
  IVON optimizer for neural networks based on variational learning.
  ☆81Updated last year
• akuhren / selective_gp
  Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".
  ☆25Updated 3 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆67Updated last year
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆52Updated last year
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆71Updated 9 months ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆109Updated last year
• chenw20 / SGPA
  Example code of Sparse Gaussian Process Attention (ICLR 2023)
  ☆26Updated 4 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆76Updated 3 years ago
• larslorch / avici
  Amortized Inference for Causal Structure Learning, NeurIPS 2022
  ☆71Updated 11 months ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆465Updated last year