A. Martini

Machine learning approaches to XANES spectra for quantitative 3D structural determination: The case of CO2 adsorption on CPO-27-Ni MOF

C. Lamberti, A. Guda, A. Soldatov, 2020 .

Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms

A. Guda, A. Soldatov, C. Copéret, 2021, npj Computational Materials.

Search for Analytical Relations between X-Ray Absorption Spectra Descriptors and the Local Atomic Structure Using Machine Learning

A. Guda, A. Soldatov, S. Guda, 2021, Journal of Surface Investigation: X-ray, Synchrotron and Neutron Techniques.

Machine learning powered by principal component descriptors as the key for sorted structural fit of XANES.

A. Guda, O. Safonova, S. Guda, 2021, Physical chemistry chemical physics : PCCP.

How Does the Solvent Control Electron Transfer? Experimental and Theoretical Studies of the Simplest Charge Transfer Reaction

Benjamin J. Schwartz, B. Schwartz, A. Martini, 2001 .

Spectroscopy and Dynamics of Nanometer-Sized Noble Metal Particles

G. Hartland, J. Hodak, A. Martini, 1998 .

Revisiting the Extended X-ray Absorption Fine Structure Fitting Procedure through a Machine Learning-Based Approach.

K. Janssens, D. D. De Vos, E. Borfecchia, 2021, The journal of physical chemistry. A.

Estimating a Set of Pure XANES Spectra from Multicomponent Chemical Mixtures Using a Transformation Matrix-Based Approach

E. Borfecchia, A. Guda, S. Guda, 2021 .

Quantitative Analysis of the UV–Vis Spectra for Gold Nanoparticles Powered by Supervised Machine Learning

A. Guda, A. Soldatov, S. Guda, 2021 .