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
  ☆463Updated last year
• f-dangel / backpack
  BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.
  ☆601Updated 3 weeks ago
• izmailovpavel / understandingbdl
  ☆251Updated 2 years ago
• facebookincubator / flowtorch
  This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…
  ☆311Updated 5 months ago
• wjmaddox / swa_gaussian
  Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
  ☆476Updated 2 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆78Updated 2 months ago
• probabilists / zuko
  Normalizing flows in PyTorch
  ☆435Updated 3 weeks ago
• lezcano / geotorch
  Constrained optimization toolkit for PyTorch
  ☆705Updated 4 months ago
• bayesiains / nflows
  Normalizing flows in PyTorch
  ☆979Updated 11 months ago
• TyXe-BDL / TyXe
  ☆155Updated 3 years ago
• team-approx-bayes / ivon
  IVON optimizer for neural networks based on variational learning.
  ☆78Updated last year
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆241Updated last year
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆463Updated 3 months ago
• normal-computing / posteriors
  Uncertainty quantification with PyTorch
  ☆377Updated 2 months 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…
  ☆57Updated 2 years ago
• ott-jax / ott
  Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
  ☆676Updated last month
• ENSTA-U2IS-AI / torch-uncertainty
  Open-source framework for uncertainty and deep learning models in PyTorch
  ☆462Updated 2 weeks ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆227Updated last year
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆51Updated 3 years ago
• tfjgeorge / nngeometry
  {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch
  ☆216Updated last week
• VincentStimper / normalizing-flows
  PyTorch implementation of normalizing flow models
  ☆917Updated last year
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆552Updated last year
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆231Updated 5 years ago
• kach / gradient-descent-the-ultimate-optimizer
  Code for our NeurIPS 2022 paper
  ☆370Updated 2 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆115Updated 3 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆275Updated 3 years ago
• didriknielsen / survae_flows
  Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"
  ☆289Updated 4 years ago
• f-dangel / curvlinops
  PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)
  ☆61Updated last month
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆181Updated 3 years ago
• google / uncertainty-baselines
  High-quality implementations of standard and SOTA methods on a variety of tasks.
  ☆1,551Updated last week