daniel-dodd

scoringrules

Scoring rules for probabilistic forecast evaluation.

torch2jax

Run PyTorch in JAX. 🤝

sgd-gp

Public code for running Stochastic Gradient Descent on GPs.

geometric_asymptotics

gptide

Gaussian Process regression toolkit for Transformation of Infrastructure through Digitial Engineering applications

cola

Compositional Linear Algebra

nnx

Neural Networks for JAX

neural-diffusion-processes

Neural Diffusion Processes

sbtm

Repository for score-based transport modeling.

GPfY

Gaussian processes with spherical harmonic features in JAX

Coin-SVGD

Code for "Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates" (ICML 2023)

matrix

Structured matrices

plum

Multiple dispatch in Python

parameterfree

Parameter-Free Optimizers for Pytorch

lineax

Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax

simple-pytree

A dead simple Python package for creating custom JAX pytree objects

equinox

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

JaxUtils

Model training utilities in JAX.

MOGPJax

Multi-output Gaussian processes in JAX.

JaxKern

Kernel functions in JAX.

t-SVGP

Codes for 'Dual Parameterization of Sparse Variational Gaussian Processes' (NeurIPS 2021)

efax

Exponential families for JAX

probnum

Probabilistic Numerics in Python.

ApproximateGPs.jl

Approximations for Gaussian processes: sparse variational inducing point approximations, Laplace approximation, ...

AbstractGPs.jl

Abstract types and methods for Gaussian Processes.

KernelFunctions.jl

Julia package for kernel functions for machine learning

JaxLinOp

Linear Operators in JAX.

GPJax

Gaussian processes in JAX.

distrax

online_vargp

Online variational GPs