Artificial Neural Network (ANN) is a type of machine learning algorithm or an information processing model consisting of elements, called artificial neurons, which are interconnected into several layers (one input layer, one or more hidden layers, and one output layer). The complex relationships between inputs and outputs are modeled during the training process using a large set of reference (experimental or theoretical) data. When trained properly, the ANN can fast generate the result based on the input data.
In our laboratory, we develop the ANNs methodology to perform the analysis of X-ray absorption data.
Example: "Neural network approach for characterizing structural transformations by x-ray absorption fine structure spectroscopy"
(from J. Timoshenko, A. Anspoks, A. Cintins, A. Kuzmin, J. Purans, A.I. Frenkel, Phys. Rev. Lett. 120 (2018) 225502:1-6.)