Schnetz
PulseAugur coverage of Schnetz — every cluster mentioning Schnetz across labs, papers, and developer communities, ranked by signal.
-
Graph Neural Network Predicts Protein Topology Using All Atom Embeddings
Researchers have developed a new method for predicting transmembrane protein topology using the SchNet graph neural network (GNN). This approach utilizes all atom-level embeddings, a departure from traditional methods t…
-
FoldPipe system streamlines molecular ML data streaming
Researchers have developed FoldPipe, a Python orchestration layer designed to improve the efficiency of training molecular machine-learning models. This system addresses challenges with retrieving large molecular graph …
-
New GNN models advance crystal property prediction and molecular simulations
Researchers have developed new graph neural network (GNN) models for predicting crystal properties. One approach, CPGN, uses a multi-scale GNN to jointly learn atomic, bond, and coordination-polyhedron representations, …
-
New neural network fuses 3D geometry, topology, and physics for molecular prediction
Researchers have developed a novel Tri-Branch Modular Fusion Neural Network designed to improve molecular property prediction. This framework integrates three distinct data modalities: 3D spatial geometry using SchNet, …