Alternatives and similar repositories for TyXe

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

• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆456Updated 11 months ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 10 months ago
• AaltoML / BayesNewton
  Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
  ☆235Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 4 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 2 months ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆222Updated 8 months ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆104Updated last year
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆34Updated 4 months ago
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆47Updated 3 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆224Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆69Updated 2 months ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆227Updated 9 months ago
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆88Updated 5 months ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆121Updated 3 years ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆181Updated 2 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated 2 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆196Updated 2 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆85Updated 8 months ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆54Updated last year
• aleximmer / Laplace
  Laplace approximations for Deep Learning.
  ☆515Updated 4 months ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 7 months ago
• AWehenkel / UMNN
  Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…
  ☆123Updated 8 months ago