Alternatives and similar repositories for VINF

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

• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆88Updated 3 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• pmorenoz / RecyclableGP
  Recyclable Gaussian Processes
  ☆11Updated 2 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• siboehm / NormalizingFlowNetwork
  Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982
  ☆21Updated 4 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• MJHutchinson / ExtrinsicGaugeIndependentVectorGPs
  A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes
  ☆25Updated 4 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆121Updated 2 years ago
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆85Updated last year
• probml / JSL
  Jax SSM Library
  ☆48Updated 2 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• microsoft / vi-hds
  Variational inference for hierarchical dynamical systems
  ☆48Updated last year
• robert-giaquinto / gradient-boosted-normalizing-flows
  We got a stew going!
  ☆27Updated 2 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• uber-research / vargp
  Variational Auto-Regressive Gaussian Processes for Continual Learning
  ☆22Updated 4 years ago
• IPL-UV / jaxkern
  A lightweight didactic library of kernel methods using the back-end JAX.
  ☆12Updated 2 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 3 years ago
• glouppe / flowing-with-jax
  ☆15Updated 4 years ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆15Updated 3 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆170Updated 3 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆18Updated 5 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 4 years ago