Alternatives and similar repositories for VAI-Lab:

Users that are interested in VAI-Lab are comparing it to the libraries listed below

• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆36Updated 5 months ago
• google-research / gpax
  ☆30Updated 6 months ago
• lbl-camera / fvGP
  A software package for flexible HPC GPs
  ☆16Updated last month
• wesselb / lab
  A generic interface for linear algebra backends
  ☆73Updated last month
• justindomke / pangolin
  probabilistic programming focused on fun
  ☆40Updated 5 months ago
• pnkraemer / probdiffeq
  Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…
  ☆44Updated this week
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆21Updated 4 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• pnkraemer / matfree
  Matrix-free linear algebra in JAX.
  ☆116Updated 2 months ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆22Updated last year
• leonard-gleyzer / connex
  Fine-grained, dynamic control of neural network topology in JAX.
  ☆21Updated last year
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆11Updated last year
• JonathanWenger / itergp
  IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
  ☆40Updated last year
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆102Updated last year
• MJHutchinson / ExtrinsicGaugeIndependentVectorGPs
  A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes
  ☆25Updated 3 years ago
• eepperly / Randomly-Pivoted-Cholesky
  Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"
  ☆28Updated 5 months ago
• google-deepmind / annealed_flow_transport
  ☆50Updated 2 years ago
• marvinpfoertner / linpde-gp
  Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"
  ☆24Updated 11 months ago
• wongswk / magi
  ☆13Updated 5 months ago
• probabilistic-numerics / probnum-spring-school
  Tutorial materials of the Probabilistic Numerics Spring School.
  ☆34Updated last year
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 8 months ago
• clayton-r / symtorch
  Initial Commit
  ☆19Updated 4 years ago
• michaelosthege / pyrff
  pyrff: Python implementation of random fourier feature approximations for gaussian processes
  ☆28Updated 2 weeks ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• NeilGirdhar / efax
  Exponential families for JAX
  ☆63Updated this week
• operalib / operalib
  Learning with operator-valued kernels
  ☆22Updated 2 years ago
• IdahoLabResearch / BIhNNs
  The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …
  ☆14Updated 2 years ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆37Updated 2 years ago
• probcomp / GenSMCP3.jl
  Automated SMC with Probabilistic Program Proposals, for the Gen PPL.
  ☆22Updated last year