Michael S Chen

Optically Induced Anisotropy in Time-Resolved Scattering: Imaging Molecular-Scale Structure and Dynamics in Disordered Media with Experiment and Theory.

T. Morawietz, Kenneth A Jung, K. Gaffney, 2022, Physical review letters.

Machine learning potentials from transfer learning of periodic correlated electronic structure methods: Application to liquid water with AFQMC, CCSD, and CCSD(T)

Timothy C. Berkelbach, Joonho Lee, D. Reichman, 2022, 2211.16619.

Exploiting Machine Learning to Efficiently Predict Multidimensional Optical Spectra in Complex Environments.

Michael S. Chen, Tim J. Zuehlsdorff, Tobias Morawietz, 2020, The journal of physical chemistry letters.

Data-Efficient Machine Learning Potentials from Transfer Learning of Periodic Correlated Electronic Structure Methods: Liquid Water at AFQMC, CCSD, and CCSD(T) Accuracy.

Timothy C. Berkelbach, Joonho Lee, D. Reichman, 2023, Journal of chemical theory and computation.

Elucidating the Role of Hydrogen Bonding in the Optical Spectroscopy of the Solvated Green Fluorescent Protein Chromophore: Using Machine Learning to Establish the Importance of High-Level Electronic Structure.

C. Isborn, T. Zuehlsdorff, Yuezhi Mao, 2023, The journal of physical chemistry letters.

AENET-LAMMPS and AENET-TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials.

T. Morawietz, Nongnuch Artrith, H. Mori, 2021, The Journal of chemical physics.

Molecular Structure Prediction Using Infrared Spectra Category : Physical Sciences , CS 229 : Fall 2017

Y. Zhu, Michael S Chen, Sophia Chen, 2017 .