F. Karsai

发表

On-the-fly machine learning force field generation: Application to melting points

Georg Kresse, Ryosuke Jinnouchi, Ferenc Karsai, 2019, Physical Review B.

Note: Molecular dynamics studies of high-density amorphous ice: influence of long-range Coulomb interactions.

F. Karsai, G. Zifferer, T. Loerting, 2012, The Journal of chemical physics.

Electron–phonon coupling in semiconductors within the GW approximation

G. Kresse, F. Karsai, M. Engel, 2018, New Journal of Physics.

α−β phase transition of zirconium predicted by on-the-fly machine-learned force field

G. Kresse, Peitao Liu, F. Karsai, 2020, Physical Review Materials.

ULTRASONOGRAPHIC DETERMINATION OF RENAL VOLUME IN THE DOG

F. Karsai, K. Vörös, T. Vrabély, 1992 .

Correlation of ultrasonographic and patho‐morphological findings in canine hepatic diseases

F. Karsai, L. Papp, K. Vörös, 1991 .

Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials

G. Kresse, Peitao Liu, R. Jinnouchi, 2021, npj Computational Materials.

Effect of cholagogues on the volume of the gallbladder of dogs.

F. Karsai, K. Vörös, Á. Sterczer, 1996, Research in veterinary science.

Changes in the serum levels of primary bile acids in dairy cows.

F. Karsai, F. Szaniszló, 1990, Acta veterinaria Hungarica.

On-the-Fly Active Learning of Interatomic Potentials for Large-Scale Atomistic Simulations.

Ryosuke Jinnouchi, Ryoji Asahi, Ferenc Karsai, 2020, The journal of physical chemistry letters.

Ab initio perspective on the Mollwo-Ivey relation for F centers in alkali halides

P. Blaha, L. Wirtz, R. Laskowski, 2015, 1507.02209.

Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111).

A. Singraber, G. Kresse, Peitao Liu, 2022, Physical review letters.

Descriptors representing two- and three-body atomic distributions and their effects on the accuracy of machine-learned inter-atomic potentials.

Ryosuke Jinnouchi, Ryoji Asahi, Ferenc Karsai, 2020, The Journal of chemical physics.

[Changes of certain parameters of fat metabolism in dairy cows during the peripartum period].

F. Karsai, T. Gaál, 1987, DTW. Deutsche tierarztliche Wochenschrift.

Fully Consistent Finite-Strain Landau Theory for High-Pressure Phase Transitions

P. Blaha, W. Schranz, F. Karsai, 2013, 1309.5306.

Proton Transport in Perfluorinated Ionomer Simulated by Machine-Learned Interatomic Potential.

G. Kresse, R. Jinnouchi, F. Karsai, 2023, The journal of physical chemistry letters.

Making free-energy calculations routine: Combining first principles with machine learning

Ryosuke Jinnouchi, Ferenc Karsai, Georg Kresse, 2020 .

Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian Inference.

Georg Kresse, Ryosuke Jinnouchi, Ferenc Karsai, 2019, Physical review letters.

On the importance of local orbitals using second energy derivatives for d and f electrons

Peter Blaha, Ferenc Karsai, Fabien Tran, 2017, Comput. Phys. Commun..

Effects of electron-phonon coupling on absorption spectrum: K edge of hexagonal boron nitride

G. Kresse, P. Blaha, F. Karsai, 2018, Physical Review B.

Ultrasonographic findings of renal dysplasia in cocker spaniels: eight cases.

F. Karsai, L. Papp, K. Vörös, 1997, Acta veterinaria Hungarica.

Peripartal fluctuations of plasma and hepatic lipid components in dairy cows.

F. Husvéth, F. Karsai, T. Gaál, 1982, Acta veterinaria Academiae Scientiarum Hungaricae.

F center in lithium fluoride revisited: Comparison of solid-state physics and quantum-chemistry approaches

David Koller, Peter Blaha, Ferenc Karsai, 2014 .

Absolute standard hydrogen electrode potential and redox potentials of atoms and molecules: machine learning aided first principles calculations

F. Karsai, Ryosuke Jinnouchi, Georg Kresse, 2024, 2409.11000.

Machine learning-aided first-principles calculations of redox potentials

G. Kresse, F. Karsai, Ryosuke Jinnouchi, 2023, npj Computational Materials.