Build Graph Nets in Tensorflow

Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

TypeDB-ML is the Machine Learning integrations library for TypeDB

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined

A toolkit for mapping networks of political and economic influence through diverse types of entities and their relations. Accessible at http://granoproject.org

[CVPR2019]Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks

[NeurIPS 2023] Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs

Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)

Graph Network for protein-protein interface

Graph convolutions in Keras with TensorFlow, PyTorch or Jax.

Reimplementation of Learning Mesh-based Simulation With Graph Networks

Implements a disparity filter in Python, based on graphs in NetworkX, to extract the multiscale backbone of a complex weighted network (Serrano, et al., 2009)

Graph Network for protein-protein interface including language model features

Graph Neural networks for NLP

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Graph Nets (GN) implement by pytorch

This project involved the analysis of the ArXiv citation network.

Explainability of Deep RL algorithms using graph networks and layer-wise relevance propagation.

Dijkstra adjacency distance matrices were calculated for 40 cities from traffic sensor locations provide by UTD19 https://utd19.ethz.ch/.

Analysis of the Symptoms-Disease Network database using communities.

The code for the NeurIPS 2019 Graph Representation Learning workshop paper "Learning Visual Dynamics Models of Rigid Objects using Relational Inductive Biases" (Ferreira et al., 2019)

IDAO-2022 semi-final solution from NESCafe Gold 3in1 team.

A PyTorch library for Graph Convolutional Networks.

Implementation of Relation Mask R-CNN with Graph Permutation Invariant Networks

Student research project on pagerank estimation with deep graph networks

1.The polymer-units(repeating units) are identified from the SMILES code of the polymer

This code is implemented according to paper "Scalable and Parallel Deep Bayesian Optimization on Attributed Graphs", accepted by TNNLS. (Python2/TensorFlow)

Repository about the projects in the course of network dynamics and learning at PoliTo

Advanced molecular analysis by converting molecular structures into graph representations.