3 papers
cs.LG2024
In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs
Grzegorz Kaszuba, Amirhossein D. Naghdi, Dario Massa +3
Large language models manifest the ability of few-shot adaptation to a sequence of provided examples. This behavior, known as in-context learning, allows for performing nontrivial…
cond-mat.mtrl-sci2024
Transfer Learning in Materials Informatics: structure-property relationships through minimal but highly informative multimodal input
Dario Massa, Grzegorz Kaszuba, Stefanos Papanikolaou +1
In this work we propose simple, effective and computationally efficient transfer learning approaches for structure-property relation predictions in the context of materials, with h…
cond-mat.mtrl-sci2023
Compositional Search of Stable Crystalline Structures in Multi-Component Alloys Using Generative Diffusion Models
Grzegorz Kaszuba, Amirhossein Naghdi Dorabati, Stefanos Papanikolaou +2
Exploring the vast composition space of multi-component alloys presents a challenging task for both \textit{ab initio} (first principles) and experimental methods due to the time-c…