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)

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)

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)

Channel Estimation for MIMO-OCDM with Fresnel Domain Pilots. - Deyu Lu; Yiyin Wang; Lingya Liu; Xiaoli Ma (ICC, 2024)

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)

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)