Repository Index

Graph and Network algorithms in Julia

Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux

• deep-learning
• deep-neural-networks
• gradient-descent
• automatic-differentiation

A platform independent tensor library with autograd for the JVM

• java
• library
• deep-neural-networks

Deep learning model for single-cell inference of multi-omic profiles from a single input modality.

• single-cell
• scrna-seq
• scatac-seq
• deep-neural-networks

Working with time-dependent networks in Julia

• graph
• evolving-graphs
• julia
• network

A Python toolkit for quantum neural networks.

PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"

Workbench for practical machine learning in Ruby.

• machine-learning
• machine-learning-algorithms
• neural-network
• neural-networks

DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.

Distributed Simulation of Transport Networks

Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.