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; et al. (Comput. Phys. Commun., 2019)

Ranking the information content of distance measures. - Aldo Glielmo; Claudio Zeni; Bingqing Cheng; Gábor Csányi; Alessandro Laio (CoRR, 2021)

BenchML: an extensible pipelining framework for benchmarking representations of materials and molecules at scale. - Carl Poelking; Felix A. Faber; Bingqing Cheng (Mach. Learn. Sci. Technol., 2022)

GAUCHE: A Library for Gaussian Processes in Chemistry. - Ryan-Rhys Griffiths; Leo Klarner; Henry B. Moss; Aditya Ravuri; Sang Truong; Yuanqi Du; Samuel Stanton; Gary Tom; Bojana Rankovic; Arian Rokkum Jamasb; Aryan Deshwal; Julius Schwartz; et al. (NeurIPS, 2023)

Cartesian atomic cluster expansion for machine learning interatomic potentials. - Bingqing Cheng (CoRR, 2024)

Response Matching for generating materials and molecules. - Bingqing Cheng (CoRR, 2024)

Latent Ewald summation for machine learning of long-range interactions. - Bingqing Cheng (CoRR, 2024)

Automatic feature selection and weighting using Differentiable Information Imbalance. - Romina Wild; Vittorio Del Tatto; Felix Wodaczek; Bingqing Cheng; Alessandro Laio (CoRR, 2024)

Learning charges and long-range interactions from energies and forces. - Dongjin Kim; Daniel S. King; Peichen Zhong; Bingqing Cheng (CoRR, 2024)

Flood Inundation Probability Estimation by Integrating Physical and Social Sensing Data: Case Study of 2021 Heavy Rainfall in Henan, China. - Wenying Du; Qingyun Xia; Bingqing Cheng; Lei Xu 032; Zeqiang Chen; Xiang Zhang 002; Min Huang 005; Nengcheng Chen (Remote. Sens., 2024)

Machine learning interatomic potential can infer electrical response. - Peichen Zhong; Dongjin Kim; Daniel S. King; Bingqing Cheng (CoRR, 2025)

A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. - Dongjin Kim; Xiaoyu Wang; Peichen Zhong; Daniel S. King; Théo Jaffrelot Inizan; Bingqing Cheng (CoRR, 2025)