rochesterxugroup / DSGPMLinks
Deep Supervised Graph Partitioning Model
☆14Updated 3 years ago
Alternatives and similar repositories for DSGPM
Users that are interested in DSGPM are comparing it to the libraries listed below
Sorting:
- Geometric super-resolution for molecular geometries☆40Updated 3 years ago
- Molecular mechanics systems and simulation data☆16Updated last year
- Library for training Gaussian Processes on Molecules☆36Updated 3 years ago
- Research repository for the proposed equivariant graph attention network that operates on large biomolecules proposed by Le et al. (2022)☆19Updated 2 years ago
- ☆40Updated 3 years ago
- A light-weight PyTorch extension for equivariant deep learning☆16Updated 4 months ago
- parameterizing valid Euclidean distance matrices (EDMs) via neural networks☆19Updated 5 years ago
- Synthetic coordinates for GNNs, as proposed in "Directional Message Passing on Molecular Graphs via Synthetic Coordinates" (NeurIPS 2021)☆30Updated 2 years ago
- Materials for the course Machine Learning for Molecular Engineering (MIT Spring 2021).☆14Updated 4 years ago
- The official implementation of Energy-Inspired Molecular Conformation Optimization (ICLR 2022)☆36Updated 2 years ago
- ☆11Updated 6 years ago
- Generative model for molecular distance geometry☆39Updated 2 years ago
- [ICLR'24] Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Molecule Generation☆23Updated 4 months ago
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆49Updated 2 years ago
- A deep learning-based framework to uniquely identify an uncorrelated, isometric and meaningful latent representation.☆17Updated last year
- Example to fit parameters and run CG simulations using TorchMD and Schnet☆46Updated 3 years ago
- Code for performing adversarial attacks on atomistic systems using NN potentials☆38Updated 2 years ago
- ☆21Updated 5 years ago
- Comparing graph representations for molecular features prediction☆24Updated last year
- Message Passing Neural Networks for Molecule Property Prediction☆24Updated 5 years ago
- cG-SchNet - a conditional generative neural network for 3d molecular structures☆61Updated 2 years ago
- Codebase for Cormorant Neural Networks☆60Updated 3 years ago
- An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming (ICML'21)☆51Updated 3 years ago
- Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.☆72Updated last year
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆43Updated last week
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆26Updated 2 years ago
- Learning Neural Generative Dynamics for Molecular Conformation Generation (ICLR 2021)☆22Updated 3 years ago
- Learning Neural Generative Dynamics for Molecular Conformation Generation (ICLR 2021)☆46Updated 3 years ago
- Contrastive pretraining to learn chemical reaction representations (RxnRep) for downstream tasks.☆33Updated 2 years ago
- MaxEnt code for fitting simulation outcomes/statistical models to observations☆16Updated 2 years ago