Alternatives and similar repositories for Laplace:

Users that are interested in Laplace 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
  ☆428Updated 4 months ago
• f-dangel / backpack
  BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.
  ☆568Updated 2 weeks ago
• facebookincubator / flowtorch
  This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…
  ☆302Updated last month
• izmailovpavel / understandingbdl
  ☆235Updated 2 years ago
• lezcano / geotorch
  Constrained optimization toolkit for PyTorch
  ☆664Updated 2 years ago
• wjmaddox / swa_gaussian
  Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
  ☆456Updated last year
• normal-computing / posteriors
  Uncertainty quantification with PyTorch
  ☆333Updated 2 months ago
• bayesiains / nflows
  Normalizing flows in PyTorch
  ☆869Updated 3 weeks ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆197Updated 2 months ago
• JaxGaussianProcesses / GPJax
  Gaussian processes in JAX.
  ☆473Updated last month
• probabilists / zuko
  Normalizing flows in PyTorch
  ☆352Updated last month
• IntelLabs / bayesian-torch
  A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
  ☆561Updated last week
• TyXe-BDL / TyXe
  ☆147Updated 2 years ago
• ott-jax / ott
  Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.
  ☆555Updated 2 weeks ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆111Updated 2 years ago
• tfjgeorge / nngeometry
  {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch
  ☆210Updated 3 months ago
• kazukiosawa / asdl
  ASDL: Automatic Second-order Differentiation Library for PyTorch
  ☆182Updated last month
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆59Updated this week
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆229Updated 4 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆271Updated 2 years ago
• didriknielsen / survae_flows
  Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"
  ☆286Updated 3 years ago
• ENSTA-U2IS-AI / torch-uncertainty
  Open-source framework for uncertainty and deep learning models in PyTorch
  ☆338Updated this week
• google / jaxopt
  Hardware accelerated, batchable and differentiable optimizers in JAX.
  ☆944Updated 4 months ago
• wilson-labs / cola
  Compositional Linear Algebra
  ☆456Updated this week
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆172Updated 2 years ago
• 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…
  ☆51Updated last year
• google-deepmind / distrax
  ☆545Updated last month
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆211Updated 7 months ago
• noahgolmant / pytorch-hessian-eigenthings
  Efficient PyTorch Hessian eigendecomposition tools!
  ☆370Updated 10 months ago
• VincentStimper / normalizing-flows
  PyTorch implementation of normalizing flow models
  ☆768Updated 4 months ago