Machine-learning Kondo physics using variational autoencoders. - Cole Miles; Matthew R. Carbone; Erica J. Sturm; Deyu Lu; Andreas Weichselbaum; Kipton Barros; Robert M. Konik (CoRR, 2021)

When not to use machine learning: a perspective on potential and limitations. - Matthew R. Carbone (CoRR, 2022)

Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. - Wei Chen 043; Yihui Ren 001; Ai Kagawa; Matthew R. Carbone; Samuel Yen-Chi Chen; Xiaohui Qu; Shinjae Yoo; Austin Clyde; Arvind Ramanathan; Rick L. Stevens; Hubertus Van Dam; Deyu Lu (ICMLA, 2023)

Decoding Structure-Spectrum Relationships with Physically Organized Latent Spaces. - Zhu Liang; Matthew R. Carbone; Wei Chen 043; Fanchen Meng; Eli Stavitski; Deyu Lu; Mark S. Hybertsen; Xiaohui Qu (CoRR, 2023)

Self-driving Multimodal Studies at User Facilities. - Phillip M. Maffettone; Daniel B. Allan; Stuart I. Campbell; Matthew R. Carbone; Thomas A. Caswell; Brian L. DeCost; Dmitri Gavrilov; Marcus D. Hanwell; Howie Joress; Joshua K. Lynch; Bruce Ravel; Stuart B. Wilkins; et al. (CoRR, 2023)

Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models. - Hyuna Kwon; Tim Hsu; Wenyu Sun; Wonseok Jeong; Fikret Aydin; James Chapman 005; Xiao Chen; Matthew R. Carbone; Deyu Lu; Fei Zhou 002; Tuan Anh Pham (CoRR, 2023)

Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files. - Matthew R. Carbone; Fanchen Meng; Christian Vorwerk; Benedikt Maurer; Fabian Peschel; Xiaohui Qu; Eli Stavitski; Claudia Draxl; John Vinson; Deyu Lu (J. Open Source Softw., 2023)

The Generalized Green's function Cluster Expansion: A Python package for simulating polarons. - Matthew R. Carbone; Stepan Fomichev; Andrew J. Millis; Mona Berciu; David R. Reichman; John Sous (J. Open Source Softw., 2023)

A Universal Deep Learning Framework for Materials X-ray Absorption Spectra. - Shubha R. Kharel; Fanchen Meng; Xiaohui Qu; Matthew R. Carbone; Deyu Lu (CoRR, 2024)

Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node. - Imran Latif; Alex C. Newkirk; Matthew R. Carbone; Arslan Munir; Yuewei Lin; Jonathan Koomey; Xi Yu; Zhiuha Dong (CoRR, 2024)

Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models. - Hyuna Kwon; Tim Hsu; Wenyu Sun; Wonseok Jeong; Fikret Aydin; James Chapman 005; Xiao Chen; Vincenzo Lordi; Matthew R. Carbone; Deyu Lu; Fei Zhou 002; Tuan Anh Pham (Mach. Learn. Sci. Technol., 2024)

Single-Node Power Demand During AI Training: Measurements on an 8-GPU NVIDIA H100 System. - Imran Latif; Alex C. Newkirk; Matthew R. Carbone; Arslan Munir; Yuewei Lin; Jonathan Koomey; Xi Yu; Zhihua Dong (IEEE Access, 2025)