Initial Structure to Relaxed Energy (IS2RE), Direct
5 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
This technical note describes the recent updates of Graphormer, including architecture design modifications, and the adaption to 3D molecular dynamics simulation.
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Despite their widespread success in various domains, Transformer networks have yet to perform well across datasets in the domain of 3D atomistic graphs such as molecules even when 3D-related inductive biases like translational invariance and rotational equivariance are considered.
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
We also obtain SOTA results on QM9, MOLPCBA, and LIT-PCBA molecular property prediction benchmarks via transfer learning.
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+
Uni-Mol+ first generates a raw 3D molecule conformation from inexpensive methods such as RDKit.
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction
Reversely, the model Reconstructs a more robust equilibrium state prediction by transforming edge-level predictions to node-level with a sphere-fitting algorithm.