Joshua J. Turner

According to our database, Joshua J. Turner authored at least 11 papers between 2022 and 2026.

Collaborative distances:

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

2026

Universal Magnetic Structure Prediction from Atomic Coordinates with Near-Experimental Accuracy.

Abhijatmedhi Chotrattanapituk, Ryotaro Okabe, Eunbi Rha, Mariya Al-Hinai, Eugene Jiang, Daniel M. Pajerowski, Yongqiang Cheng, Joshua J. Turner, Mingda Li

CoRR, May, 2026

Probing Non-Equilibrium Grain Boundary Dynamics with XPCS and Domain-Adaptive Machine Learning.

Mouyang Cheng, Bowen Yu, Chu-Liang Fu, Nina Andrejevic, Matthias T. Agne, Riley Hanus, Qiwei Wan, Nathan C. Drucker, Thanh Nguyen, Andrei Fluerasu, Lutz Wiegart, Xiaoqian M. Chen, Daniel Pajerowski, Yongqiang Cheng, Joshua J. Turner, G. Jeffrey Snyder, Mingda Li

CoRR, May, 2026

2025

Detail Across Scales: Multi-Scale Enhancement for Full Spectrum Neural Representations.

Yuan Ni, Zhantao Chen, Cheng Peng, Rajan Plumley, Chun Hong Yoon, Jana B. Thayer, Joshua J. Turner

CoRR, September, 2025

Physics-guided dual implicit neural representations for source separation.

Yuan Ni, Zhantao Chen, Alexander N. Petsch, Edmund Xu, Cheng Peng, Alexander I. Kolesnikov, Sugata Chowdhury, Arun Bansil, Jana B. Thayer, Joshua J. Turner

Mach. Learn. Sci. Technol., 2025

2024

Kernel fusion in atomistic spin dynamics simulations on Nvidia GPUs using tensor core.

Hongwei Chen, Shiyang Chen, Joshua J. Turner, Adrian E. Feiguin

J. Comput. Sci., 2024

2023

Bayesian experimental design and parameter estimation for ultrafast spin dynamics.

Zhantao Chen, Cheng Peng, Alexander N. Petsch, Sathya R. Chitturi, Alana Okullo, Sugata Chowdhury, Chun Hong Yoon, Joshua J. Turner

Mach. Learn. Sci. Technol., December, 2023

A high-performance implementation of atomistic spin dynamics simulations on x86 CPUs.

Hongwei Chen, Yujia Zhai, Joshua J. Turner, Adrian E. Feiguin

Comput. Phys. Commun., October, 2023

Augmenting x-ray single particle imaging reconstruction with self-supervised machine learning.

Zhantao Chen, Cong Wang, Mingye Gao, Chun Hong Yoon, Jana B. Thayer, Joshua J. Turner

CoRR, 2023

Machine learning enabled experimental design and parameter estimation for ultrafast spin dynamics.

Zhantao Chen, Cheng Peng, Alexander N. Petsch, Sathya R. Chitturi, Alana Okullo, Sugata Chowdhury, Chun Hong Yoon, Joshua J. Turner

CoRR, 2023

Capturing dynamical correlations using implicit neural representations.

Sathya R. Chitturi, Zhurun Ji, Alexander Petsch, Cheng Peng, Zhantao Chen, Rajan Plumley, Mike Dunne, Sougata Mardanya, Sugata Chowdhury, Hongwei Chen, Arun Bansil, Adrian E. Feiguin, Alexander Kolesnikov, Dharmalingam Prabhakaran, Stephen Hayden, Daniel Ratner, Chunjing Jia, Youssef Nashed, Joshua J. Turner

CoRR, 2023

2022

Testing the data framework for an AI algorithm in preparation for high data rate X-ray facilities.

Hongwei Chen, Sathya R. Chitturi, Rajan Plumley, Lingjia Shen, Nathan C. Drucker, Nicolas Burdet, Cheng Peng, Sougata Mardanya, Daniel Ratner, Aashwin Mishra, Chun Hong Yoon, Sanghoon Song, Matthieu Chollet, Gilberto Fabbris, Mike Dunne, Silke Nelson, Mingda Li, Aaron Lindenberg, Chunjing Jia, Youssef Nashed, Arun Bansil, Sugata Chowdhury, Adrian E. Feiguin, Joshua J. Turner, Jana Thayer

Proceedings of the 4th Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing, 2022