niklasschmitz

ad-kernels

Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"

DifferentiableDFTK

Automatic differentiation for density functional theory in Julia.

sdf_jax

Utilities for neural signed distance fields in JAX.

DFTK.jl

Density-functional toolkit

AbstractGPs.jl

Abstract types and methods for Gaussian Processes.

adventofcode

http://adventofcode.com/

blackjax

BlackJAX is a sampling library designed for ease of use, speed and modularity.

blog

ChainRules.jl

forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

ChainRulesCore.jl

It is like recipes but for AD! (Full functionality is in ChainRules.jl but this a light weight dependency just to define sensitivities for your functions in your packages)

ChainRulesDeclarationHelpers.jl

Helpers for declaring ChainRules

deepchem

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

dex-lang

Research language for array processing in the Haskell/ML family

DftFunctionals.jl

Interface and Julia implementation of exchange-correlation functionals

DiffOpt.jl

Differentiating convex optimization program w.r.t. program parameters

Diffractor.jl

Next-generation AD

Distances.jl

A Julia package for evaluating distances (metrics) between vectors.

elegy

A High Level API for Deep Learning in JAX

fax

ForwardDiff.jl

Forward Mode Automatic Differentiation for Julia

GalacticOptim.jl

Local, global, and beyond optimization for scientific machine learning (SciML)

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

Graphs.jl

An optimized graphs package for the Julia programming language

instant-ngp

Instant neural graphics primitives: lightning fast NeRF and more

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

jax-md

Differentiable, Hardware Accelerated, Molecular Dynamics

maml-jax

Implementation of Model-Agnostic Meta-Learning (MAML) in Jax

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

robfun_team_gold

Robotics: Fundamentals project course work

Zygote.jl

Intimate Affection Auditor