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Molecular Property Prediction

Predict molecular properties from structures or representations to support molecular screening and model evaluation.

25 resources

PhysNet

Model

PhysNet is a TensorFlow implementation of a neural network for predicting molecular energies, forces, dipole moments and partial charges, with a configurable training workflow and an example dataset.

Open sourcePython

Molecular Property Prediction · Quantum Chemistry

Updated

TorchMD-Net

Model

TorchMD-Net implements trainable neural network potentials as PyTorch modules, with TensorNet architectures, custom molecular datasets, pretrained checkpoint loading and molecular dynamics integrations.

Open sourcePython

Molecular Property Prediction · Computational Chemistry

Updated

TorchANI

Model

TorchANI is a PyTorch library for developing, training and using ANI-style neural network interatomic potentials, with optional C++ and CUDA extensions for descriptors and inference.

Open sourcePythonC++

Molecular Property Prediction · Quantum Chemistry

Updated

SchNetPack

Model

SchNetPack is a Python toolkit for building and training atomistic neural networks, with SchNet and PaiNN representations, quantum-chemical property outputs, and molecular dynamics components.

Open sourcePython

Molecular Property Prediction · Quantum Chemistry

Updated

Chemprop

Model

Chemprop is a PyTorch-based toolkit for training and evaluating message-passing neural networks for molecular property prediction, with CLI workflows, Python modules and task-specific notebooks.

Open sourcePython

Molecular Property Prediction

Updated