2 papers
cond-mat.mtrl-sci2026
Transformer Atomic Cluster Expansion: TRACE
Paramvir Ahlawat
Designing machine-learning interatomic potentials involves achieving the precise representation of complex many-body interactions alongside the efficiency required for scalable mol…
cond-mat.mtrl-sci2025
Thermal Conductivity Predictions with Foundation Atomistic Models
Balázs Póta, Paramvir Ahlawat, Gábor Csányi +1
Advances in machine learning have led to the development of foundation models for atomistic materials chemistry, enabling quantum-accurate descriptions of interatomic forces across…