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Yusuf Hamied Department of Chemistry

 

Lars Schaaf

Publications

A foundation model for atomistic materials chemistry
I Batatia, P Benner, Y Chiang, AM Elena, DP Kovács, J Riebesell, XR Advincula, M Asta, M Avaylon, WJ Baldwin, F Berger, N Bernstein, A Bhowmik, SM Blau, V Cărare, JP Darby, S De, FD Pia, VL Deringer, R Elijošius, Z El-Machachi, F Falcioni, E Fako, AC Ferrari, A Genreith-Schriever, J George, REA Goodall, CP Grey, P Grigorev, S Han, W Handley, HH Heenen, K Hermansson, C Holm, J Jaafar, S Hofmann, KS Jakob, H Jung, V Kapil, AD Kaplan, N Karimitari, JR Kermode, N Kroupa, J Kullgren, MC Kuner, D Kuryla, G Liepuoniute, JT Margraf, I-B Magdău, A Michaelides, JH Moore, AA Naik, SP Niblett, SW Norwood, N O'Neill, C Ortner, KA Persson, K Reuter, AS Rosen, LL Schaaf, C Schran, BX Shi, E Sivonxay, TK Stenczel, V Svahn, C Sutton, TD Swinburne, J Tilly, CVD Oord, E Varga-Umbrich, T Vegge, M Vondrák, Y Wang, WC Witt, F Zills, G Csányi
(2023)
(link to publication)
Equivariant Matrix Function Neural Networks
I Batatia, LL Schaaf, H Chen, G Csányi, C Ortner, FA Faber
(2023)
(doi: 10.48550/arxiv.2310.10434)
(link to publication)
Accurate energy barriers for catalytic reaction pathways: an automatic training protocol for machine learning force fields
LL Schaaf, E Fako, S De, A Schäfer, G Csányi
– npj Computational Materials
(2023)
9,
180
(doi: 10.1038/s41524-023-01124-2)
Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields
LL Schaaf, E Fako, S De, A Schäfer, G Csányi
– npj Computational Materials
(2023)
9,
180
(doi: 10.1038/s41524-023-01124-2)
Accurate Energy Barriers for Catalytic Reaction Pathways: An Automatic Training Protocol for Machine Learning Force Fields
L Schaaf, E Fako, S De, A Schäfer, G Csányi
(2023)
(doi: 10.48550/arxiv.2301.09931)
(link to publication)

Research Group

Email address

lls34@cam.ac.uk

College

Wolfson College

    Study at Cambridge

    About the University

    Research at Cambridge