Matthew R. Carbone

发表

Effective traplike activated dynamics in a continuous landscape.

Marco Baity-Jesi, Matthew R. Carbone, Valerio Astuti, 2020, Physical review. E.

Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships

Santosh K. Suram, Brian A. Rohr, Yang Ha, 2020, npj Computational Materials.

Classification of local chemical environments from x-ray absorption spectra using supervised machine learning

Shinjae Yoo, Mehmet Topsakal, Matthew R. Carbone, 2019, Physical Review Materials.

Machine learning of Kondo physics using variational autoencoders and symbolic regression

Kipton Barros, Cole Miles, Matthew R. Carbone, 2021, Physical Review B.

Machine-learning Kondo physics using variational autoencoders pdf

Kipton Barros, Cole Miles, Matthew R. Carbone, 2021, ArXiv.

Competition between energy- and entropy-driven activation in glasses.

Matthew R. Carbone, M. Baity-Jesi, 2022, Physical review. E.

Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships

Brian A. Rohr, Matthew R. Carbone, Steven B. Torrisi, 2020, npj Computational Materials.

Machine-Learning X-Ray Absorption Spectra to Quantitative Accuracy.

Matthew R. Carbone, D. Lu, M. Topsakal, 2020, Physical review letters.

Machine learning the spectral function of a hole in a quantum antiferromagnet

Matthew R. Carbone, Jackson Lee, Wei-Hang Yin, 2023, Physical Review B.

Bond-Peierls polaron: Moderate mass enhancement and current-carrying ground state

Matthew R. Carbone, D. Reichman, A. Millis, 2021, Physical Review B.

Microscopic model of the doping dependence of linewidths in monolayer transition metal dichalcogenides.

Matthew R. Carbone, D. Reichman, M. Mayers, 2020, The Journal of chemical physics.

Self-driving Multimodal Studies at User Facilities

Brian L. DeCost, Matthew R. Carbone, Phillip M. Maffettone, 2023, Acta Crystallographica Section A Foundations and Advances.

Uncertainty-aware predictions of molecular x-ray absorption spectra using neural network ensembles

Matthew R. Carbone, D. Lu, M. Hybertsen, 2022, Physical Review Research.

Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

Matthew R. Carbone, D. Lu, Nongnuch Artrith, 2023, Scientific data.

Numerically exact generalized Green's function cluster expansions for electron-phonon problems

Matthew R. Carbone, D. Reichman, J. Sous, 2021, Physical Review B.

Decoding Structure-Spectrum Relationships with Physically Organized Latent Spaces

Matthew R. Carbone, D. Lu, M. Hybertsen, 2023, Physical Review Materials.

When not to use machine learning: A perspective on potential and limitations

Matthew R. Carbone, M. R. Carbone, 2022, MRS Bulletin.

Predicting impurity spectral functions using machine learning

Matthew R. Carbone, Erica J. Sturm, D. Lu, 2020, 2011.10719.

Accurate, Uncertainty-Aware Classification of Molecular Chemical Motifs from Multimodal X-ray Absorption Spectroscopy.

Matthew R. Carbone, Phillip M. Maffettone, D. Lu, 2023, The journal of physical chemistry. A.

Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files

Matthew R. Carbone, D. Lu, C. Ambrosch-Draxl, 2022, J. Open Source Softw..

Dynamical processes in the condensed phase: methods and models

Matthew R. Carbone, 2021 .

Physically interpretable approximations of many-body spectral functions

Matthew R. Carbone, K. Barros, Shubhangi Goswami, 2023, 2306.11038.

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Matthew R. Carbone, D. Lu, T. Pham, 2023, The Journal of Physical Chemistry C.

Atomic Insights into the Oxidative Degradation Mechanisms of Sulfide Solid Electrolytes

Matthew R. Carbone, Nongnuch Artrith, Yonghua Du, 2023, 2310.00794.

Flexible formulation of value for experiment interpretation and design

Matthew R. Carbone, Phillip M. Maffettone, H. Joress, 2023, Matter.

Emulating Expert Insight: A Robust Strategy for Optimal Experimental Design

Brian L. DeCost, Matthew R. Carbone, Phillip M. Maffettone, 2023, 2307.13871.

Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models

Matthew R. Carbone, Fikret Aydin, Xiao Chen, 2023, 2312.05472.

Transferable Graph Neural Fingerprint Models for Quick Response to Future Bio-Threats

Matthew R. Carbone, Austin R. Clyde, D. Lu, 2023, 2023 International Conference on Machine Learning and Applications (ICMLA).

Crystal structures of (R S)-N-[(1R,2S)-2-benzyloxy-1-(2,6-dimethylphenyl)propyl]-2-methylpropane-2-sulfinamide and (R S)-N-[(1S,2R)-2-benzyloxy-1-(2,4,6-trimethylphenyl)propyl]-2-methylpropane-2-sulfinamide: two related protected 1,2-amino alcohols

Matthew R. Carbone, D. Weix, L. Papa, 2014, Acta crystallographica. Section E, Structure reports online.