Matthew R. Carbone

13 papers C 1Journal 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
Single-Node Power Demand During AI Training: Measurements on an 8-GPU NVIDIA H100 System.
IEEE Access
Imran Latif, Alex C. Newkirk, Matthew R. Carbone, Arslan Munir, Yuewei Lin, Jonathan Koomey, Xi Yu, Zhihua Dong
2024 J jnl
A Universal Deep Learning Framework for Materials X-ray Absorption Spectra.
CoRR
Shubha R. Kharel, Fanchen Meng, Xiaohui Qu, Matthew R. Carbone, Deyu Lu
2024 J jnl
Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node.
CoRR
Imran Latif, Alex C. Newkirk, Matthew R. Carbone, Arslan Munir, Yuewei Lin, Jonathan Koomey, Xi Yu, Zhiuha Dong
2024 J jnl
Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models.
Mach. Learn. Sci. Technol.
Hyuna Kwon, Tim Hsu, Wenyu Sun, Wonseok Jeong, Fikret Aydin, James Chapman, Xiao Chen, Vincenzo Lordi, Matthew R. Carbone, Deyu Lu, Fei Zhou, Tuan Anh Pham
2023 J jnl
Decoding Structure-Spectrum Relationships with Physically Organized Latent Spaces.
CoRR
Zhu Liang, Matthew R. Carbone, Wei Chen, Fanchen Meng, Eli Stavitski, Deyu Lu, Mark S. Hybertsen, Xiaohui Qu
2023 J jnl
Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files.
J. Open Source Softw.
Matthew R. Carbone, Fanchen Meng, Christian Vorwerk, Benedikt Maurer, Fabian Peschel, Xiaohui Qu, Eli Stavitski, Claudia Draxl, John Vinson, Deyu Lu
2023 J jnl
Self-driving Multimodal Studies at User Facilities.
CoRR
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, Jakub Wlodek, Daniel Olds
2023 J jnl
Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models.
CoRR
Hyuna Kwon, Tim Hsu, Wenyu Sun, Wonseok Jeong, Fikret Aydin, James Chapman, Xiao Chen, Matthew R. Carbone, Deyu Lu, Fei Zhou, Tuan Anh Pham
2023 J jnl
The Generalized Green's function Cluster Expansion: A Python package for simulating polarons.
J. Open Source Softw.
Matthew R. Carbone, Stepan Fomichev, Andrew J. Millis, Mona Berciu, David R. Reichman, John Sous
2023 C conf
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats.
ICMLA
Wei Chen, Yihui Ren, 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
2023 J jnl
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats.
CoRR
Wei Chen, Yihui Ren, Ai Kagawa, Matthew R. Carbone, Samuel Yen-Chi Chen, Xiaohui Qu, Shinjae Yoo, Austin Clyde, Arvind Ramanathan, Rick L. Stevens, Hubertus Johannes Jacobus Van Dam, Deyu Lu
2022 J jnl
When not to use machine learning: a perspective on potential and limitations.
CoRR
Matthew R. Carbone
2021 J jnl
Machine-learning Kondo physics using variational autoencoders.
CoRR
Cole Miles, Matthew R. Carbone, Erica J. Sturm, Deyu Lu, Andreas Weichselbaum, Kipton Barros, Robert M. Konik