5 citations · 6 across the 3 of their papers we have counts for
5 papers
Does Pretraining Teach Chemical Language Models Chemistry?
Leif Sieben, Yoel Zimmermann
Chemical language models (CLMs) are pretrained on large corpora of molecules with the aim of learning representations that transfer to diverse downstream tasks. Here, we systematic…
BranchIP: Learning Adaptive Equivariant Computation for Interatomic Potentials
Laura Zichi, Gil Harari, Chuin Wei Tan +6
Equivariant machine learning interatomic potentials (MLIPs) have revolutionized atomistic modeling, but accurate treatment of complex materials and molecular systems demands expens…
Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials
Gil Harari, Yoel Zimmermann, Ola Tangen Kulseng +4
Machine learning interatomic potentials (MLIPs) have become a hallmark of AI for scientific simulation. While efforts on new architectures and datasets have led to increasingly acc…
Quantum Acoustics Demystifies the Strange Metals
Eric J. Heller, Alhun Aydin, Anton M. Graf +11
Phonons have long been thought to be incapable of explaining key phenomena in strange metals, including linear-in-\textit{T} Planckian resistivity from high to very low temperature…
Rise and Fall of Anderson Localization by Lattice Vibrations: A Time-Dependent Machine Learning Approach
Yoel Zimmermann, Joonas Keski-Rahkonen, Anton M. Graf +1
The intricate relationship between electrons and the crystal lattice is a linchpin in condensed matter, traditionally described by the Fröhlich model encompassing the lowest-order…