Data-driven modeling of S→ S1 excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design
Derivatives of BODIPY are popular fluorophores due to their synthetic feasibility, structural
rigidity, high quantum yield, and tunable spectroscopic properties. While the characteristic …
rigidity, high quantum yield, and tunable spectroscopic properties. While the characteristic …
The resolution-vs.-accuracy dilemma in machine learning modeling of electronic excitation spectra
In this study, we explore the potential of machine learning for modeling molecular electronic
spectral intensities as a continuous function in a given wavelength range. Since presently …
spectral intensities as a continuous function in a given wavelength range. Since presently …
Information-theoretic symmetry classifications of crystal patterns in the presence of noise and strong Fedorov type pseudosymmetries for an optimal subsequent …
P Moeck - arXiv preprint arXiv:2108.00829, 2021 - arxiv.org
Statistically sound crystallographic symmetry classifications are obtained with information
theory based methods in the presence of approximately Gaussian distributed noise. A set of …
theory based methods in the presence of approximately Gaussian distributed noise. A set of …