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Matthew R. Carbone
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2020 – today
- 2024
- [j3]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:
Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models. Mach. Learn. Sci. Technol. 5(4): 45037 (2024) - [i7]Shubha R. Kharel, Fanchen Meng, Xiaohui Qu, Matthew R. Carbone, Deyu Lu:
A Universal Deep Learning Framework for Materials X-ray Absorption Spectra. CoRR abs/2409.19552 (2024) - 2023
- [j2]Matthew R. Carbone, Fanchen Meng, Christian Vorwerk, Benedikt Maurer, Fabian Peschel, Xiaohui Qu, Eli Stavitski, Claudia Draxl, John Vinson, Deyu Lu:
Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files. J. Open Source Softw. 8(87): 5182 (2023) - [j1]Matthew R. Carbone, Stepan Fomichev, Andrew J. Millis, Mona Berciu, David R. Reichman, John Sous:
The Generalized Green's function Cluster Expansion: A Python package for simulating polarons. J. Open Source Softw. 8(90): 5115 (2023) - [c1]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:
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. ICMLA 2023: 800-807 - [i6]Zhu Liang, Matthew R. Carbone, Wei Chen, Fanchen Meng, Eli Stavitski, Deyu Lu, Mark S. Hybertsen, Xiaohui Qu:
Decoding Structure-Spectrum Relationships with Physically Organized Latent Spaces. CoRR abs/2301.04724 (2023) - [i5]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:
Self-driving Multimodal Studies at User Facilities. CoRR abs/2301.09177 (2023) - [i4]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:
Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats. CoRR abs/2308.01921 (2023) - [i3]Hyuna Kwon, Tim Hsu, Wenyu Sun, Wonseok Jeong, Fikret Aydin, James Chapman, Xiao Chen, Matthew R. Carbone, Deyu Lu, Fei Zhou, Tuan Anh Pham:
Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models. CoRR abs/2312.05472 (2023) - 2022
- [i2]Matthew R. Carbone:
When not to use machine learning: a perspective on potential and limitations. CoRR abs/2210.02666 (2022) - 2021
- [i1]Cole Miles, Matthew R. Carbone, Erica J. Sturm, Deyu Lu, Andreas Weichselbaum, Kipton Barros, Robert M. Konik:
Machine-learning Kondo physics using variational autoencoders. CoRR abs/2107.08013 (2021)
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last updated on 2024-12-02 22:34 CET by the dblp team
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