Repository Index

Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

• autodiff
• deep-learning
• machine-learning
• rust

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...

• java
• gpu
• deeplearning
• neural-nets

Efficiently computes derivatives of NumPy code.

• autograd
• automatic-differentiation
• numpy
• python

A PyTorch Library for Accelerating 3D Deep Learning Research

• pytorch
• 3d-deep-learning
• neural-networks
• differentiable-rendering

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

• quantum
• machine-learning
• deep-learning
• neural-network

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

• differential-equations
• differentialequations
• julia
• ode

Message Passing Neural Networks for Molecule Property Prediction

• machine-learning
• chemistry
• neural-networks
• drug-discovery

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

• python
• genetic-algorithm
• optimization
• numpy

Owl - OCaml Scientific Computing @ https://ocaml.xyz

• matrix
• linear-algebra
• ndarray
• statistical-functions

Brian is a free, open source simulator for spiking neural networks.

• python
• neuroscience
• science
• differential-equations

Python package for graph neural networks in chemistry and biology

• deep-learning
• graph-neural-networks
• dgl
• cheminformatics

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

• deep-learning
• pytorch
• deep-chemistry
• graph-neural-network

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research

• computational-chemistry
• computational-biology
• deep-learning
• deep-neural-networks

Chainer Chemistry: A Library for Deep Learning in Biology and Chemistry

• deep-learning
• chemistry
• neural-network
• biology

DiffSharp: Differentiable Functional Programming

• machine-learning
• tensor
• dotnet
• autodiff

A Euclidean diffusion model for structure-based drug design.

• ddpm
• drug-design
• equivariance
• generative-model

Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

• histopathology-images
• microscopy
• sliding-windows
• medical-image-analysis

Sequential regulatory activity predictions with deep convolutional neural networks.

Neural networks toolbox focused on medical image analysis

• python
• keras
• convolutional-neural-networks
• brain

GraphDTA: Predicting drug-target binding affinity with graph neural networks

Source code for "DeepDTA: deep drug-target binding affinity prediction"

• protein-ligand-interactions
• convolutional-neural-networks

RNA-seq prediction with deep convolutional neural networks.

The V Tensor Library

• v
• hacktoberfest
• autograd
• deep-learning

Optimising chemical reactions using machine learning

• chemistry
• machine-learning
• optimization
• bayesian-optimization