Gábor Csányi

35 papers A* 4A 1Journal 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Better without U: Impact of Selective Hubbard U Correction on Foundational MLIPs. CoRR Thomas Warford, Fabian L. Thiemann, Gábor Csányi
2026	J	`jnl`	Design Space of Self-Consistent Electrostatic Machine Learning Interatomic Potentials. CoRR William J. Baldwin, Ilyes Batatia, Martin Vondrák, Johannes T. Margraf, Gábor Csányi
2026	J	`jnl`	MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry. CoRR Ilyes Batatia, William J. Baldwin, Domantas Kuryla, Joseph Hart, Elliott Kasoar, Alin M. Elena, Harry Moore, Mikolaj J. Gawkowski, Benjamin X. Shi, Venkat Kapil, Panagiotis Kourtis, Ioan-Bogdan Magdau, Gábor Csányi
2025	J	`jnl`	A practical guide to machine learning interatomic potentials - Status and future. CoRR Ryan Jacobs, Dane Morgan, Siamak Attarian, Jun Meng, Chen Shen, Zhenghao Wu, Clare Yijia Xie, Julia H. Yang, Nongnuch Artrith, Ben Blaiszik, Gerbrand Ceder, Kamal Choudhary, Gábor Csányi, Ekin Dogus Cubuk, Bowen Deng, Ralf Drautz, Xiang Fu, Jonathan Godwin, Vasant G. Honavar, Olexandr Isayev, Anders Johansson, Boris Kozinsky, Stefano Martiniani, Shyue Ping Ong, Igor Poltavsky, K. J. Schmidt, So Takamoto, Aidan Thompson, Julia Westermayr, Brandon M. Wood
2025	A	`conf`	Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. HPDC Jesun Sahariar Firoz, Franco Pellegrini, Mario Geiger, Darren Hsu, Jenna A. Bilbrey, Han-Yi Chou, Maximilian Stadler, Markus Höhnerbach, Tingyu Wang, Dejun Lin, Emine Küçükbenli, Henry W. Sprueill, Ilyes Batatia, Sotiris S. Xantheas, MalSoon Lee, Christopher J. Mundy, Gábor Csányi, Justin S. Smith, Ponnuswamy Sadayappan, Sutanay Choudhury
2025	J	`jnl`	Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. CoRR Jesun Firoz, Franco Pellegrini, Mario Geiger, Darren Hsu, Jenna A. Bilbrey, Han-Yi Chou, Maximilian Stadler, Markus Hoehnerbach, Tingyu Wang, Dejun Lin, Emine Küçükbenli, Henry W. Sprueill, Ilyes Batatia, Sotiris S. Xantheas, MalSoon Lee, Chris Mundy, Gábor Csányi, Justin S. Smith, Ponnuswamy Sadayappan, Sutanay Choudhury
2025	J	`jnl`	Resonances in reflective Hamiltonian Monte Carlo. CoRR Namu Kroupa, Gábor Csányi, Will Handley
2025	J	`jnl`	The design space of E(3)-equivariant atom-centred interatomic potentials. Nat. Mac. Intell. Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
2024	J	`jnl`	Accurate Crystal Structure Prediction of New 2D Hybrid Organic Inorganic Perovskites. CoRR Nima Karimitari, William J. Baldwin, Evan W. Muller, Zachary J. L. Bare, W. Joshua Kennedy, Gábor Csányi, Christopher Sutton
2024	J	`jnl`	Benchmarking of machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces. Mach. Learn. Sci. Technol. Wojciech G. Stark, Cas van der Oord, Ilyes Batatia, Yaolong Zhang, Bin Jiang, Gábor Csányi, Reinhard Johann Maurer
2024	A*	`conf`	Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials. ICLR Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram S. Deshpande
2024	J	`jnl`	Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials. CoRR Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram S. Deshpande
2024	A*	`conf`	Equivariant Matrix Function Neural Networks. ICLR Ilyes Batatia, Lars L. Schaaf, Gábor Csányi, Christoph Ortner, Felix A. Faber
2024	J	`jnl`	Zero Shot Molecular Generation via Similarity Kernels. CoRR Rokas Elijosius, Fabian Zills, Ilyes Batatia, Sam Walton Norwood, Dávid Péter Kovács, Christian Holm, Gábor Csányi
2023	J	`jnl`	Equivariant Matrix Function Neural Networks. CoRR Ilyes Batatia, Lars L. Schaaf, Huajie Chen, Gábor Csányi, Christoph Ortner, Felix A. Faber
2023	J	`jnl`	Machine learning of microscopic structure-dynamics relationships in complex molecular systems. Mach. Learn. Sci. Technol. Martina Crippa, Annalisa Cardellini, Matteo Cioni, Gábor Csányi, Giovanni M. Pavan
2022	J	`jnl`	Atomic cluster expansion: Completeness, efficiency and stability. J. Comput. Phys. Geneviève Dusson, Markus Bachmayr, Gábor Csányi, Ralf Drautz, Simon Etter, Cas van der Oord, Christoph Ortner
2022	J	`jnl`	Kernel charge equilibration: efficient and accurate prediction of molecular dipole moments with a machine-learning enhanced electron density model. Mach. Learn. Sci. Technol. Carsten G. Staacke, Simon Wengert, Christian Kunkel, Gábor Csányi, Karsten Reuter, Johannes T. Margraf
2022	A*	`conf`	MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields. NeurIPS Ilyes Batatia, Dávid Péter Kovács, Gregor N. C. Simm, Christoph Ortner, Gábor Csányi
2022	J	`jnl`	MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields. CoRR Ilyes Batatia, Dávid Péter Kovács, Gregor N. C. Simm, Christoph Ortner, Gábor Csányi
2022	J	`jnl`	Tensor-reduced atomic density representations. CoRR James P. Darby, Dávid Péter Kovács, Ilyes Batatia, Miguel A. Caro, Gus L. W. Hart, Christoph Ortner, Gábor Csányi
2022	J	`jnl`	The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials. CoRR Ilyes Batatia, Simon L. Batzner, Dávid Péter Kovács, Albert Musaelian, Gregor N. C. Simm, Ralf Drautz, Christoph Ortner, Boris Kozinsky, Gábor Csányi
2021	J	`jnl`	Atomic permutationally invariant polynomials for fitting molecular force fields. Mach. Learn. Sci. Technol. Alice E. A. Allen, Geneviève Dusson, Christoph Ortner, Gábor Csányi
2021	J	`jnl`	Predicting polarizabilities of silicon clusters using local chemical environments. Mach. Learn. Sci. Technol. Mario G. Zauchner, Stefano Dal Forno, Gábor Csányi, Andrew P. Horsfield, Johannes Lischner
2021	J	`jnl`	Ranking the information content of distance measures. CoRR Aldo Glielmo, Claudio Zeni, Bingqing Cheng, Gábor Csányi, Alessandro Laio
2021	A*	`conf`	Symmetry-Aware Actor-Critic for 3D Molecular Design. ICLR Gregor N. C. Simm, Robert Pinsler, Gábor Csányi, José Miguel Hernández-Lobato
2020	J	`jnl`	An Experimentally Driven Automated Machine Learned lnter-Atomic Potential for a Refractory Oxide. CoRR Ganesh Sivaraman, Leighanne Gallington, Anand Narayanan Krishnamoorthy, Marius Stan, Gábor Csányi, Álvaro Vázquez-Mayagoitia, Chris J. Benmore
2020	J	`jnl`	Regularised atomic body-ordered permutation-invariant polynomials for the construction of interatomic potentials. Mach. Learn. Sci. Technol. Cas van der Oord, Geneviève Dusson, Gábor Csányi, Christoph Ortner
2020	J	`jnl`	Symmetry-Aware Actor-Critic for 3D Molecular Design. CoRR Gregor N. C. Simm, Robert Pinsler, Gábor Csányi, José Miguel Hernández-Lobato
2019	J	`jnl`	Approximation of Potential Energy Surfaces with Spherical Harmonics. CoRR Markus Bachmayr, Gábor Csányi, Geneviève Dusson, Simon Etter, Cas van der Oord, Christoph Ortner
2019	J	`jnl`	Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide. CoRR Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur, Christian Holm, Marius Stan, Gábor Csányi, Chris J. Benmore, Álvaro Vázquez-Mayagoitia
2016	J	`jnl`	Exploiting molecular dynamics in Nested Sampling simulations of small peptides. Comput. Phys. Commun. Nikolas S. Burkoff, Robert J. N. Baldock, Csilla Várnai, David L. Wild, Gábor Csányi
2015	J	`jnl`	The adaptive buffered force QM/MM method in the CP2K and AMBER software packages. J. Comput. Chem. Letif Mones, Andrew Jones, Andreas W. Götz, Teodoro Laino, Ross C. Walker, Ben Leimkuhler, Gábor Csányi, Noam Bernstein
2011	J	`jnl`	Diffusive nested sampling. Stat. Comput. Brendon J. Brewer, Lívia B. Pártay, Gábor Csányi
2007	J	`jnl`	Gaussian Processes: A Method for Automatic QSAR Modeling of ADME Properties. J. Chem. Inf. Model. Olga Obrezanova, Gábor Csányi, Joelle M. R. Gola, Matthew D. Segall