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Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide.

G. Sivaraman, A. Krishnamoorthy, M. Baur, C. Holm, M. Stan, G. Csányi, C. Benmore, and Á. Vázquez-Mayagoitia. CoRR, (2019)

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Tibor Gábori

Gábor Hegyi

Gábor Köller

Gábor Jüttner

Gábor Worseck

Other publications of authors with the same name

Constant-pressure nested sampling with atomistic dynamicsR. Baldock, N. Bernstein, K. Salerno, L. Pártay, and G. Csányi. Physical Review E, 96 (4): 043311 (October 2017)Predicting polarizabilities of silicon clusters using local chemical environments.M. Zauchner, S. Forno, G. Csányi, A. Horsfield, and J. Lischner. Mach. Learn. Sci. Technol., 2 (4): 45029 (2021)MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields.I. Batatia, D. Kovács, G. Simm, C. Ortner, and G. Csányi. NeurIPS, (2022)Symmetry-Aware Actor-Critic for 3D Molecular Design.G. Simm, R. Pinsler, G. Csányi, and J. Hernández-Lobato. ICLR, OpenReview.net, (2021)Accurate Crystal Structure Prediction of New 2D Hybrid Organic Inorganic Perovskites.N. Karimitari, W. Baldwin, E. Muller, Z. Bare, W. Kennedy, G. Csányi, and C. Sutton. CoRR, (2024)Exploiting molecular dynamics in Nested Sampling simulations of small peptides.N. Burkoff, R. Baldock, C. Várnai, D. Wild, and G. Csányi. Comput. Phys. Commun., (2016)Ranking the information content of distance measures.A. Glielmo, C. Zeni, B. Cheng, G. Csányi, and A. Laio. CoRR, (2021)Kernel charge equilibration: efficient and accurate prediction of molecular dipole moments with a machine-learning enhanced electron density model.C. Staacke, S. Wengert, C. Kunkel, G. Csányi, K. Reuter, and J. Margraf. Mach. Learn. Sci. Technol., 3 (1): 15032 (2022)Equivariant Matrix Function Neural Networks.I. Batatia, L. Schaaf, H. Chen, G. Csányi, C. Ortner, and F. Faber. CoRR, (2023)Zero Shot Molecular Generation via Similarity Kernels.R. Elijosius, F. Zills, I. Batatia, S. Norwood, D. Kovács, C. Holm, and G. Csányi. CoRR, (2024)

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Disambiguation of "Csányi, Gábor"

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Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide.

Please choose a person to relate this publication to

Tibor Gábori

Gábor Hegyi

Gábor Köller

Gábor Jüttner

Gábor Worseck

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Csányi, Gábor"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide.

Please choose a person to relate this publication to

Tibor Gábori

Gábor Hegyi

Gábor Köller

Gábor Jüttner

Gábor Worseck

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
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Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide.