Gábor Cśanyi
- A foundation model for atomistic materials chemistry
2023/12/29 by Ilyes Batatia, Philipp Benner, Batatia, Ilyes +182 · 5 voices · 147 citations
Materials Science · Decision Sciences · #physics.chem-ph #cond-mat.mtrl-sci
- Gaussian approximation potentials: A brief tutorial introduction
2015/04/27 by Albert P. Bartók, Gábor Cśanyi, Gábor Csányi · 46 citations
Materials Science · Biochemistry, Genetics and Molecular Biology · Computer Science · #Machine Learning in Materials Science #Protein Structure and Dynamics #Computational Drug Discovery Methods
- Performance and Cost Assessment of Machine Learning Interatomic Potentials
2020/01/09 by Yunxing Zuo, Chi Chen, Xiangguo Li +8 · 34 citations
Chemistry · Materials Science · #Crystallography and molecular interactions #Machine Learning in Materials Science #X-ray Diffraction in Crystallography
- MACE-OFF: Transferable Short Range Machine Learning Force Fields for Organic Molecules
2023/12/23 by Dávid Péter Kovács, Kovács, Dávid Péter, J. Harry Moore +20 · 1 voice · 42 citations
Biochemistry, Genetics and Molecular Biology · Chemistry · Materials Science · #Machine Learning in Materials Science #Mass Spectrometry Techniques and Applications #Protein Structure and Dynamics #physics.chem-ph
- Gaussian Process Regression for Materials and Molecules
2021/08/16 by Volker L. Deringer, Albert P. Bartók, Noam Bernstein +3 · 33 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Computational Drug Discovery Methods #Machine Learning in Materials Science #Protein Structure and Dynamics
- Nested sampling for physical scientists
2022/05/26 by Greg Ashton, G. Ashton, Noam Bernstein +30 · 1 voice · 9 citations
Computer Science · Mathematics · Physics and Astronomy · #Cosmology and Gravitation Theories #Gaussian Processes and Bayesian Inference #Statistical Mechanics and Entropy #astro-ph.CO #astro-ph.IM #cond-mat.mtrl-sci #hep-ph #stat.CO
- Data-efficient fine-tuning of foundational models for first-principles quality sublimation enthalpies
2024/05/30 by Harveen Kaur, Kaur, Harveen, Flaviano Della Pia +15 · 13 citations
Chemistry · Materials Science · #Chemical Physics (physics.chem-ph) #Chemical Thermodynamics and Molecular Structure #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Thermal and Kinetic Analysis #thermodynamics and calorimetric analyses
- Diffusive nested sampling
2010/08/24 by Brendon J. Brewer, Lívia B. Pártay, Livia B. Pártay +2 · 4 citations
Mathematics · Physics and Astronomy · #Markov Chains and Monte Carlo Methods #Statistical Mechanics and Entropy #Theoretical and Computational Physics
- Efficient sampling of atomic configurational spaces
2009/06/18 by Lívia B. Pártay, Pártay, Livia B., Albert P. Bartók +3 · 4 citations
Materials Science · Biochemistry, Genetics and Molecular Biology · #Crystallization and Solubility Studies #Protein Structure and Dynamics #Machine Learning in Materials Science
- Gaussian Approximation Potentials: theory, software implementation and application examples
2023/10/05 by Sascha Klawohn, Klawohn, Sascha, Gábor Cśanyi +8 · 7 citations
Earth and Planetary Sciences · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Geophysics and Gravity Measurements #Materials Science (cond-mat.mtrl-sci) #Scientific Research and Discoveries
- Tensor product expansions for correlation in quantum many-body systems
1998/05/29 by Gábor Cśanyi, T. A. Arias, Csanyi, Gabor +1 · 2 citations
Physics and Astronomy · #Advanced Chemical Physics Studies #Cold Atom Physics and Bose-Einstein Condensates #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Quantum and electron transport phenomena #Strongly Correlated Electrons (cond-mat.str-el)
- Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023
2025/01/01 by Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva +23 · 1 voice · 5 citations
Materials Science · Computer Science · #Machine Learning in Materials Science #Computational Drug Discovery Methods #Nuclear Materials and Properties
- Accurate Crystal Structure Prediction of New 2D Hybrid Organic Inorganic Perovskites
2024/03/11 by Nima Karimitari, Karimitari, Nima, William J. Baldwin +11 · 2 citations
Engineering · Materials Science · #Conducting polymers and applications #Covalent Organic Framework Applications #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci) #Perovskite Materials and Applications