Numerical integration using Wang-Landau sampling. - Ying Wai Li; Thomas Wüst; David P. Landau; H. Q. Lin (Comput. Phys. Commun., 2007)

Monte Carlo simulations of the HP model (the "Ising model" of protein folding). - Ying Wai Li; Thomas Wüst; David P. Landau (Comput. Phys. Commun., 2011)

Using C++ AMP to Accelerate HPC Applications on Multiple Platforms. - M. Graham Lopez; Christopher Bergstrom; Ying Wai Li; Wael R. Elwasif; Oscar R. Hernandez (ISC Workshops, 2016)

Delayed Update Algorithms for Quantum Monte Carlo Simulation on GPU: Extended Abstract. - Tyler McDaniel; Eduardo F. D'Azevedo; Ying Wai Li; Paul R. C. Kent; Ming Wong; Kwai Wong (XSEDE, 2016)

A Histogram-Free Multicanonical Monte Carlo Algorithm for the Basis Expansion of Density of States. - Ying Wai Li; Markus Eisenbach 002 (PASC, 2017)

Accelerating DCA++ (Dynamical Cluster Approximation) Scientific Application on the Summit Supercomputer. - Giovanni Balduzzi; Arghya Chatterjee 001; Ying Wai Li; Peter W. Doak; Urs R. Hähner; Eduardo F. D'Azevedo; Thomas A. Maier; Thomas C. Schulthess (PACT, 2019)

Fast, scalable and accurate finite-element based ab initio calculations using mixed precision computing: 46 PFLOPS simulation of a metallic dislocation system. - Sambit Das; Phani Motamarri; Vikram Gavini; Bruno Turcksin; Ying Wai Li; Brent Leback (SC, 2019)

A greedy constructive algorithm for the optimization of neural network architectures. - Massimiliano Lupo Pasini; Junqi Yin; Ying Wai Li; Markus Eisenbach 002 (CoRR, 2019)

Histogram-free multicanonical Monte Carlo sampling to calculate the density of states. - Alfred C. K. Farris; Ying Wai Li; Markus Eisenbach 002 (Comput. Phys. Commun., 2019)

Pre-exascale accelerated application development: The ORNL Summit experience. - Lixiang Luo; Tjerk P. Straatsma; Luis Enrique Aguilar-Suárez; Ria Broer; Dmytro Bykov; Eduardo F. D'Azevedo; Shirin S. Faraji; Kalyana C. Gottiparthi; Coen de Graaf; James Austin Harris; Remco W. A. Havenith; Hans Jørgen Aagard Jensen; et al. (IBM J. Res. Dev., 2020)

Machine-Learning Accelerated Studies of Materials with High Performance and Edge Computing. - Ying Wai Li; Peter W. Doak; Giovanni Balduzzi; Wael R. Elwasif; Eduardo F. D'Azevedo; Thomas A. Maier (SMC, 2021)

Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics. - Dewi Yokelson; Nikolay V. Tkachenko; Robert Robey; Ying Wai Li; Pavel A. Dub (CoRR, 2021)

A scalable algorithm for the optimization of neural network architectures. - Massimiliano Lupo Pasini; Junqi Yin; Ying Wai Li; Markus Eisenbach 002 (Parallel Comput., 2021)

Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics on CPUs and GPUs. - Dewi Yokelson; Nikolay V. Tkachenko; Robert Robey; Ying Wai Li; Pavel A. Dub (J. Chem. Inf. Model., 2022)

HPC Application Performance Prediction with Machine Learning on New Architectures. - Dewi Yokelson; Marc Robert Joseph Charest; Ying Wai Li (PERMAVOST@HPDC, 2023)

Uncertainty-driven dynamics for active learning of interatomic potentials. - Maksim Kulichenko; Kipton Barros; Nicholas Lubbers; Ying Wai Li; Richard A. Messerly; Sergei Tretiak; Justin S. Smith; Benjamin T. Nebgen (Nat. Comput. Sci., 2023)

Model-diff: A Tool for Comparative Study of Language Models in the Input Space. - Weitang Liu; Yuelei Li; Ying Wai Li; Zihan Wang 001; Jingbo Shang (CoRR, 2024)

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates. - Anjana Anu Talapatra; Anup Pandey; Matthew S. Wilson; Ying Wai Li; Ghanshyam Pilania; Blas Pedro Uberuaga; Danny Perez (Comput. Phys. Commun., 2025)

Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials. - Sakib Matin; Emily Shinkle; Yulia Pimonova; Galen T. Craven; Aleksandra Pachalieva; Ying Wai Li; Kipton Barros; Nicholas Lubbers (CoRR, 2025)

exa-AMD: A Scalable Workflow for Accelerating AI-Assisted Materials Discovery and Design. - Maxim Moraru; Weiyi Xia; Zhuo Ye; Feng Zhang; Yongxin Yao; Ying Wai Li; Cai-Zhuang Wang (CoRR, 2025)