3 papers
q-bio.QM2026
Fold-CP: A Context Parallelism Framework for Biomolecular Modeling
Dejun Lin, Simon Chu, Vishanth Iyer +35
Understanding cellular machinery requires atomic-scale reconstruction of large biomolecular assemblies. However, predicting the structures of these systems has been constrained by…
cs.DC2025
Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE
Jesun Firoz, Franco Pellegrini, Mario Geiger +17
Chemistry Foundation Models (CFMs) that leverage Graph Neural Networks (GNNs) operating on 3D molecular graph structures are becoming indispensable tools for computational chemists…
cs.LG2024
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
Peter St. John, Dejun Lin, Polina Binder +89
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increas…