Alternatives and similar repositories for curvlinops

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

• team-approx-bayes / ivon
  IVON optimizer for neural networks based on variational learning.
  ☆80Updated last year
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆70Updated 8 months ago
• andres-fr / skerch
  Sketched linear operations for PyTorch
  ☆100Updated 2 months ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆108Updated last year
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆92Updated 10 months ago
• tfjgeorge / nngeometry
  {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch
  ☆216Updated 3 weeks ago
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆94Updated 2 years ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆152Updated last month
• kazukiosawa / asdl
  ASDL: Automatic Second-order Differentiation Library for PyTorch
  ☆191Updated last year
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆43Updated 7 months ago
• bremen79 / parameterfree
  Parameter-Free Optimizers for Pytorch
  ☆130Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆25Updated 3 years ago
• baumgach / tue-slurm-helloworld
  Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container
  ☆33Updated 2 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆79Updated 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
• probabilists / lampe
  Likelihood-free AMortized Posterior Estimation with PyTorch
  ☆131Updated last year
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆53Updated 2 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆105Updated 2 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆121Updated 3 weeks ago
• f-dangel / phd-thesis
  Source code for my PhD thesis: Backpropagation Beyond the Gradient
  ☆20Updated 2 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆52Updated 4 months ago
• aleximmer / Laplace
  Laplace approximations for Deep Learning.
  ☆531Updated 8 months ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆35Updated 4 months ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆124Updated 5 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆462Updated last year