satrialoka / gnn-from-scratch

Related projects: ⓘ

• AntonioLonga / AdvancePyTorchGeometricTutorials
  here you can find the material used for our Tutorials
  ☆93Updated 2 years ago
• zjost / blog_code
  A repo for holding example code
  ☆146Updated last year
• paulmorio / geo2dr
  Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.
  ☆44Updated last year
• gncs / molgym
  Reinforcement Learning for Molecular Design Guided by Quantum Mechanics
  ☆118Updated last year
• aimat-lab / gcnn_keras
  Graph convolutions in Keras with TensorFlow, PyTorch or Jax.
  ☆105Updated 4 months ago
• google-research / graph-attribution
  Codebase for Evaluating Attribution for Graph Neural Networks.
  ☆73Updated 3 years ago
• linafaik08 / graph_neural_networks
  ☆31Updated 2 years ago
• futianfan / reinforced-genetic-algorithm
  Structure-based Drug Design; Reinforcement Learning and Genetic Algorithm
  ☆66Updated last year
• benatorc / OTGNN
  OTGNN code
  ☆54Updated 4 years ago
• njmarko / machine-learning-with-graphs
  My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)
  ☆27Updated 2 years ago
• risilab / Autobahn
  Repository for Autobahn: Automorphism Based Graph Neural Networks
  ☆30Updated 2 years ago
• teddykoker / mpnn-for-quantum-chem
  Pytorch implementation of MPNN for Quantum Chemistry
  ☆12Updated 2 years ago
• gcucurull / jax-gcn
  Graph Convolutional Networks in JAX
  ☆30Updated 3 years ago
• mengliu1998 / awesome-expressive-gnn
  A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
  ☆124Updated 10 months ago
• rusty1s / himp-gnn
  Hierarchical Inter-Message Passing for Learning on Molecular Graphs
  ☆76Updated 2 years ago
• Ryan-Rhys / Constrained-Bayesian-Optimisation-for-Automatic-Chemical-Design
  Code to accompany the paper "Constrained Bayesian Optimisation for Automatic Chemical Design" https://pubs.rsc.org/en/content/articlehtml…
  ☆49Updated last year
• gmum / graph-representations
  Comparing graph representations for molecular features prediction
  ☆20Updated last year
• ellisalicante / GraphRewiring-Tutorial
  This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…
  ☆52Updated last year
• AntonioLonga / Explaining-the-Explainers-in-Graph-Neural-Networks
  Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"
  ☆33Updated 11 months ago
• deepfindr / gvae
  ☆85Updated last year
• shionhonda / gae-dgl
  Reimplementation of Graph Autoencoder by Kipf & Welling with DGL.
  ☆65Updated last year
• olsson-group / RL-GraphINVENT
  RL-GraphINVENT is a platform for graph-based targeted molecular generation using graph neural networks and reinforcement learning. RL-Gra…
  ☆66Updated last year
• aryandeshwal / LADDER
  Python implementation for Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces.
  ☆13Updated 2 years ago
• seokhokang / graphvae_approx
  Efficient Learning of Non-Autoregressive Graph Variational Autoencoders for Molecular Graph Generation
  ☆38Updated 4 years ago
• georgelamb19 / chempropBayes
  Bayesian MPNNs for Molecular Property Prediction
  ☆27Updated 3 years ago
• gmh14 / data_efficient_grammar
  [ICLR 2022] Data-Efficient Graph Grammar Learning for Molecular Generation
  ☆93Updated last year
• kfzyqin / Implementation-MolGAN-PyTorch
  PyTorch implementation of MolGAN: MolGAN: An implicit generative model for small molecular graphs.
  ☆50Updated 3 years ago
• Ryan-Rhys / Heteroscedastic-BO
  Heteroscedastic Bayesian Optimisation in Numpy
  ☆21Updated last year
• edvardlindelof / graph-neural-networks-for-drug-discovery
  ☆94Updated 4 years ago
• nec-research / Adaptive-Message-Passing
  Official Repository of Adaptive Message Passing
  ☆15Updated 5 months ago