M-R-Schaefer's Stars
AUTOMATIC1111/stable-diffusion-webui
Stable Diffusion web UI
tesseract-ocr/tesseract
Tesseract Open Source OCR Engine (main repository)
aristocratos/btop
A monitor of resources
arogozhnikov/einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
danielegrattarola/spektral
Graph Neural Networks with Keras and Tensorflow 2.
dask/distributed
A distributed task scheduler for Dask
tensorflow/gnn
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
jax-md/jax-md
Differentiable, Hardware Accelerated, Molecular Dynamics
neurreps/awesome-neural-geometry
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
google-deepmind/chex
ACEsuit/mace
MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
CrawlScript/tf_geometric
Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x
BayesWatch/nas-without-training
Code for Neural Architecture Search without Training (ICML 2021)
patrick-kidger/mkposters
Make posters from Markdown files.
google/CommonLoopUtils
CLU lets you write beautiful training loops in JAX.
jacobjinkelly/easy-neural-ode
Code for the paper "Learning Differential Equations that are Easy to Solve"
e3nn/e3nn-jax
jax library for E3 Equivariant Neural Networks
lab-cosmo/chemiscope
An interactive structure/property explorer for materials and molecules
cfinlay/ffjord-rnode
Regularized Neural ODEs (RNODE)
sayakpaul/Sharpness-Aware-Minimization-TensorFlow
Implements sharpness-aware minimization (https://arxiv.org/abs/2010.01412) in TensorFlow 2.
dholzmueller/bmdal_reg
Deep Batch Active Learning for Regression
cagrikymk/JAX-ReaxFF
JAX-ReaxFF: A Gradient Based Framework for Extremely Fast Optimization of Reactive Force Fields
cp2k/cp2k-input-tools
Fully validating pure-python CP2K input file tools including preprocessing capabilities
tummfm/difftre
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
lab-cosmo/kernel-tutorials
A set of utilities and pedagogic notebooks for the use of linear and kernel methods in atomistic modeling
fabiannagel/schnax
An implementation of SchNet in JAX and JAX-MD.
tummfm/jax-dimenet
Jax / Haiku implementation of DimeNet++.
Madsen-s-research-group/neuralil-public-releases
Public releases of the NeuralIL differentiable neural-network force field
sirmarcel/asax
ase + jax-md = asax
ChristianOrr/simple-jax-to-tensorrt-example
A MNIST model is defined and trained in Jax, then converted to TensorRT for inference.