2 citations · 3 across the 3 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2026★ 2 cited
Discovery and recovery of crystalline materials with property-conditioned transformers
Cyprien Bone, Matthew Walker, Bradley A. A. Martin +6
Generative models have recently shown great promise for accelerating the design and discovery of new functional materials. Conditional generation enhances this capacity by allowing…
cond-mat.mtrl-sci2026
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models
Isabel Creed, Tim Rein, Ingvars Vitenburgs +21
Machine-learned interatomic potentials (MLIPs) have had a profound impact on molecular modelling in recent years, promising to resolve the long-standing tension between the scale a…
cond-mat.mtrl-sci2026★ 1 cited
General Learning of the Electric Response of Inorganic Materials
Bradley A. A. Martin, Alex M. Ganose, Venkat Kapil +2
We introduce \texttt{MACE-Field}, a field-aware, -equivariant interatomic potential that learns a single electric enthalpy functional an…