37 citations · 95 across the 7 of their papers we have counts for
3 papers · 1 filter
A strategic roadmap for an atomistic machine-learning ecosystem
Jörg Behler, Michele Ceriotti, Cecilia Clementi +47
Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of matter is particularly widespre…
Metatensor and metatomic: foundational libraries for interoperable atomistic machine learning
Filippo Bigi, Joseph W. Abbott, Philip Loche +12
Incorporation of machine learning (ML) techniques into atomic-scale modeling has proven to be an extremely effective strategy to improve the accuracy and reduce the computational c…
Compositional Analysis of Fragrance Accords Using Femtosecond Thermal Lens Spectroscopy
Rohit Goswami, Ashwini Kumar Rawat, Sonaly Goswami +1
Femtosecond thermal lens spectroscopy (FTLS) is a powerful analytical tool, yet its application to complex, multi-component mixtures like fragrance accords remains limited. Here, w…