▥ RowanPlatforms Rowan is a cloud platform for molecular calculations, combining quantum chemistry, machine-learned potentials, property prediction, and protein–ligand workflows through a web interface and Python API. Computational Chemistry · Quantum Chemistry
◇ DeePKSModel DeePKS-kit is a Python toolkit for training quantum-chemistry energy functionals, testing post-HF models, and running self-consistent calculations through the DeePHF and DeePKS schemes. Open sourcePython Quantum Chemistry
◇ DeePTBModel DeePTB is a Python package for deep-learning electronic-structure models, combining environment-dependent tight binding with equivariant Hamiltonian, density-matrix and overlap-matrix representations. Open sourcePython Quantum Chemistry · Materials Discovery
⌥ QMLOpen Source QML is an archived Python toolkit for quantum machine learning with Fortran-backed representation, kernel and solver modules. Further development has moved to qmllib. Open sourcePython Molecular Property Prediction · Quantum Chemistry
☁ QCArchiveAPI QCArchive supports running, storing and sharing quantum chemistry calculations through a database-backed server, a Python client and computation workers maintained in one repository. Open sourcePython Quantum Chemistry · Scientific Data
▤ SPICEDataset SPICE provides quantum-mechanical energies, forces and other molecular properties for training machine learning potentials, with an emphasis on drug-like molecules and protein interactions. Open source Quantum Chemistry · Scientific Data
▤ ANI-1Dataset ANI-1 provides calculated off-equilibrium molecular conformations, with Python readers for accessing HDF5 files containing coordinates and energies for organic molecules. Open sourcePython Quantum Chemistry
◇ DimeNetModel DimeNet provides reference implementations of DimeNet and DimeNet++ for directional message passing on molecular graphs, with training notebooks, test-set prediction workflows and pretrained models. Python Molecular Property Prediction · Quantum Chemistry
◇ SpookyNetModel SpookyNet is a Python research package described as learning force fields with electronic degrees of freedom and nonlocal effects, with a cited publication and MIT-licensed repository code. Open sourcePython Molecular Property Prediction · Quantum Chemistry
◇ PhysNetModel 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
◇ TorchANIModel 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
◇ SchNetPackModel 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