Pinned Repositories
DFTK.jl
Density-functional toolkit
ad-kernels
Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"
DeepQLearning
small experiments with agents learning atari games, implemented in jax/numpy
DifferentiableDFTK
Automatic differentiation for density functional theory in Julia.
sdf_jax
Utilities for neural signed distance fields in JAX.
suptoday
simple sms bot listing club nights
niklasschmitz's Repositories
niklasschmitz/ad-kernels
Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"
niklasschmitz/DifferentiableDFTK
Automatic differentiation for density functional theory in Julia.
niklasschmitz/sdf_jax
Utilities for neural signed distance fields in JAX.
niklasschmitz/DFTK.jl
Density-functional toolkit
niklasschmitz/AbstractGPs.jl
Abstract types and methods for Gaussian Processes.
niklasschmitz/adventofcode
http://adventofcode.com/
niklasschmitz/blackjax
BlackJAX is a sampling library designed for ease of use, speed and modularity.
niklasschmitz/blog
niklasschmitz/ChainRules.jl
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
niklasschmitz/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)
niklasschmitz/ChainRulesDeclarationHelpers.jl
Helpers for declaring ChainRules
niklasschmitz/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
niklasschmitz/dex-lang
Research language for array processing in the Haskell/ML family
niklasschmitz/DftFunctionals.jl
Interface and Julia implementation of exchange-correlation functionals
niklasschmitz/DifferentiationInterface.jl
An interface to various automatic differentiation backends in Julia.
niklasschmitz/DiffOpt.jl
Differentiating convex optimization program w.r.t. program parameters
niklasschmitz/Diffractor.jl
Next-generation AD
niklasschmitz/elegy
A High Level API for Deep Learning in JAX
niklasschmitz/fax
niklasschmitz/ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
niklasschmitz/GalacticOptim.jl
Local, global, and beyond optimization for scientific machine learning (SciML)
niklasschmitz/gpytorch
A highly efficient and modular implementation of Gaussian Processes in PyTorch
niklasschmitz/Graphs.jl
An optimized graphs package for the Julia programming language
niklasschmitz/instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
niklasschmitz/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
niklasschmitz/jax-md
Differentiable, Hardware Accelerated, Molecular Dynamics
niklasschmitz/juliacon2024-physicsinformed-autodiff
niklasschmitz/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
niklasschmitz/robfun_team_gold
Robotics: Fundamentals project course work
niklasschmitz/Zygote.jl
Intimate Affection Auditor