26 citations · 52 across the 9 of their papers we have counts for
5 papers · 1 filter
Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A study employing Multifidelity Machine Learning
Dongyu Lyu, Matthias Holzenkamp, Vivin Vinod +5
Natural light-harvesting antenna complexes efficiently capture solar energy using chlorophyll, i.e., magnesium porphyrin pigments, embedded in a protein matrix. Inspired by this na…
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Vivin Vinod, Peter Zaspel
Recent progress in machine learning (ML) has made high-accuracy quantum chemistry (QC) calculations more accessible. Of particular interest are multifidelity machine learning (MFML…
Benchmarking Data Efficiency in -ML and Multifidelity Models for Quantum Chemistry
Vivin Vinod, Peter Zaspel
The development of machine learning (ML) methods has made quantum chemistry (QC) calculations more accessible by reducing the compute cost incurred in conventional QC methods. This…
Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties
Vivin Vinod, Peter Zaspel
Multifidelity machine learning (MFML) for quantum chemical (QC) properties has seen strong development in the recent years. The method has been shown to reduce the cost of generati…
QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules
Vivin Vinod, Peter Zaspel
Progress in both Machine Learning (ML) and Quantum Chemistry (QC) methods have resulted in high accuracy ML models for QC properties. Datasets such as MD17 and WS22 have been used…