An atom-bond transformer-based message passing neural network for molecular property prediction.
-
Updated
Mar 8, 2023 - Python
#
mpnn
Here are 14 public repositories matching this topic...
Predicting properties of small molecules using MPNN on QM9 dataset
-
Updated
Feb 16, 2024 - Jupyter Notebook
Official Implementation of Multi-Masked Aggregators for Graph Neural Networks in Pytorch and PyTorch Geometric
aggregator mask message-passing mma gcn geometric-deep-learning graph-attention-networks node-classification graphneuralnetwork pna mpnn graphrepresentationlearning multimaskaggregators principalneighborhoodaggregators graph-regression
-
Updated
Mar 24, 2023 - Python
Multiscale exploration of informative latent features for accurate deep eutectic solvents viscosity prediction
-
Updated
Jun 16, 2026 - Python
Graph Neural Network creation module, implemented in Tensorflow 2 with examples using the module and the iGNNition library for fast GNN prototyping.
tensorflow graphs quantum-chemistry graph-convolutional-networks gnn graph-neural-network quantum-chemistry-qm9 radio-resource-management scalable-radio-resource qm9 mpnn message-passing-neural-network
-
Updated
Jun 17, 2021 - Python
Melty Molecule is a molecular property prediction system that leverages graph neural networks to predict melting points of chemical compounds. The model uses a hybrid architecture combining Principal Neighborhood Aggregation (PNA) and Graph Isomorphism Networks (GIN) with edge updates and virtual node connectivity.
graph-neural-networks streamlit torch-geometric mpnn message-passing-neural-network molecular-property-prediction graph-isomorphism-networks melting-point-prediction
-
Updated
Jan 10, 2026 - Python
This project implements mechanisms to mitigate over-squashing, improving GNN performance on tasks requiring deep Networks.
-
Updated
Oct 20, 2026 - Python
Scaffold-split benchmark suite for ADMET property prediction (hERG, solubility, CYP3A4, Caco-2, clearance) with Morgan FP+RF and MPNN baselines, plus ECE/calibration metrics for uncertainty-aware evaluation. PyTorch · RDKit · DeepChem · scikit-learn.
benchmark machine-learning cheminformatics scikit-learn pytorch calibration computational-chemistry drug-discovery rdkit uncertainty-quantification graph-neural-networks deepchem admet mpnn molecular-property-prediction scaffold-splitting
-
Updated
Jul 4, 2026
A message-passing neural network (MPNN) model for predicting molecular sigma-profiles from SMILES strings. The model supports two prediction modes: MSE model and Composite model.
-
Updated
Aug 16, 2026 - Python
A Continuous Kernel Message Passing Neural Network (MPNN) utilizing Dynamic Filter Generation to explicitly model continuous interatomic distances. Achieves accuracy (R^2 > 0.9) on the OQMD database for predicting quantum properties, offering a 10^6x speedup over DFT simulations.
-
Updated
Jan 13, 2026 - Jupyter Notebook
Exploring numerous natural language processing techniques for antimicrobial peptide sequences.
-
Updated
Oct 10, 2024 - Jupyter Notebook
Seven graph neural networks (GCN, MPNN, DCNN, GIN, GAT, GraphSAGE, AttentiveFP) in PyTorch Geometric for molecular property prediction: ESOL solubility from SMILES, with train/predict CLI and tests.
deep-learning cheminformatics pytorch gin drug-discovery rdkit gcn dcnn graphsage graph-neural-networks moleculenet gat pytorch-geometric gnn esol solubility-prediction mpnn message-passing-neural-network molecular-property-prediction attentivefp
-
Updated
Oct 18, 2026 - Python
A Message-passing neural network (MPNN) for molecular property prediction
-
Updated
Sep 17, 2026 - Python
Add this topic to your repo
To associate your repository with the mpnn topic, visit your repo's landing page and select "manage topics."