Igor Poltavsky

According to our database, Igor Poltavsky authored at least 5 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions.

Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price, Victor Posligua, Stephan Roche, O. Anatole von Lilienfeld, Konstantin S. Novoselov, Xavier Bresson, Gianmarco Mengaldo, Xudong Chen, Terence J. O'Kane, Emily R. Lines, Matthew J. Allen, Amandine E. Debus, Clayton Miller, Jiayu Zhou, Hiroko H. Dodge, David Rousseau, Andrey Ustyuzhanin, Ziyun Yan, Mario Lanza, Fabio Sciarrino, Ryo Yoshida, Zhidong Leong, Teck Leong Tan, Qianxiao Li, Adil Kabylda, Igor Poltavsky, Alexandre Tkatchenko, Sherif Abdulkader Tawfik, Prathami Divakar Kamath, Théo Jaffrelot Inizan, Kristin A. Persson, Bryant Y. Li, Vir Karan, Chenru Duan, Haojun Jia, Qiyuan Zhao, Hiroyuki Hayashi, Atsuto Seko, Isao Tanaka, Omar M. Yaghi, Tim Gould, Bun Chan, Stefan Vuckovic, Tianbo Li, Min Lin, Zehcen Tang, Yang Li, Yong Xu, Amrita Joshi, Xiaonan Wang, Leonard W. T. Ng, Sergei V. Kalinin, Mahshid Ahmadi, Jiyizhe Zhang, Shuyuan Zhang, Alexei A. Lapkin, Ming Xiao, Zhe Wu, Kedar Hippalgaonkar, Limsoon Wong, Lorenzo Bastonero, Nicola Marzari, Dorye Luis Esteras Cordoba, Andrei Tomut, Alba Quinones Andrade, Jose-Hugo Garcia

CoRR, November, 2025

A practical guide to machine learning interatomic potentials - Status and future.

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

CoRR, March, 2025

Atomic orbits in molecules and materials for improving machine learning force fields.

Anton Charkin-Gorbulin, Artem Kokorin, Huziel E. Sauceda, Stefan Chmiela, Claudio Quarti, David Beljonne, Alexandre Tkatchenko, Igor Poltavsky

Mach. Learn. Sci. Technol., 2025

2019

i-PI 2.0: A universal force engine for advanced molecular simulations.

Venkat Kapil, Mariana Rossi, Ondrej Marsalek, Riccardo Petraglia, Yair Litman, Thomas Spura, Bingqing Cheng, Alice Cuzzocrea, Robert H. Meißner, David M. Wilkins, Benjamin A. Helfrecht, Przemyslaw Juda, Sébastien P. Bienvenue, Wei Fang, Jan Kessler, Igor Poltavsky, Steven Vandenbrande, Jelle Wieme, Michele Ceriotti

Comput. Phys. Commun., 2019

sGDML: Constructing accurate and data efficient molecular force fields using machine learning.

Stefan Chmiela, Huziel Enoc Sauceda Felix, Igor Poltavsky, Klaus-Robert Müller, Alexandre Tkatchenko

Comput. Phys. Commun., 2019