Repository Index

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

• drug-discovery
• quantum-chemistry
• deep-learning
• biology

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

Accelerated deep learning R&D

• deep-learning
• reinforcement-learning
• machine-learning
• computer-vision

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

MLBox is a powerful Automated Machine Learning python library.

• machine-learning
• auto-ml
• kaggle
• deep-learning

Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving

• self-driving-car
• tensorflow
• reinforcement-learning
• unreal-engine

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

• hpc
• workflow
• workflow-automation
• workflow-management

Python package for graph neural networks in chemistry and biology

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

TensorFlow Implementation for Computing a Semantically Segmented Bird's Eye View (BEV) Image Given the Images of Multiple Vehicle-Mounted Cameras.

• computer-vision
• machine-learning
• deep-learning
• autonomous-vehicles

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

Graph-linked unified embedding for single-cell multi-omics data integration

• bioinformatics
• deep-learning
• single-cell
• single-cell-multiomics

Tools for computational pathology

• machine-learning
• digital-pathology
• computational-pathology
• biomedical-image-processing

Maze Applied Reinforcement Learning Framework

• reinforcement-learning
• python
• machine-learning
• simulation

Automated 3D cell detection in very large images

• microscopy
• cell-detection
• deep-learning
• image-analysis

PyTorch Connectomics: segmentation toolbox for EM connectomics

• computer-vision
• neuroscience
• connectomics
• pytorch

ChemML is a machine learning and informatics program suite for the chemical and materials sciences.

• quantum-mechanics
• materials-informatics
• data-science
• machine-learning

A tool for cell instance aware segmentation in densely packed 3D volumetric images

• segmentation
• deep-learning
• bioinformatics
• neural-network

NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions

• computational-biology
• bioinformatics
• graph-convolution
• deep-learning

Cryptographic Dataset Generation & Modelling Framework

• cryptography
• deep-learning
• deep-neural-networks
• machine-learning

Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.

• alphafold3
• docking
• drug-design
• drug-discovery

Accurate segmentation of bacterial microscope images using deep learning synthetically generated image data.

• microscopy
• image-processing
• segmentation
• biology