43 citations · 51 across the 9 of their papers we have counts for
9 papers
Identification of high-reliability regions of machine learning predictions in materials science using transparent conducting oxides and perovskites as examples
Evan M. Askanazi, Emanuel A. Lazar, Ilya Grinberg
Progress in the application of machine learning (ML) methods to materials design is hindered by the lack of understanding of the reliability of ML predictions, in particular for th…
Distance-based Analysis of Machine Learning Prediction Reliability for Datasets in Materials Science and Other Fields
Evan Askanazi, Ilya Grinberg
Despite successful use in a wide variety of disciplines for data analysis and prediction, machine learning (ML) methods suffer from a lack of understanding of the reliability of pr…
Measurement of the Parity-Odd Angular Distribution of Gamma Rays From Polarized Neutron Capture on Cl
N. Fomin, R. Alarcon, L. Alonzi +61
We report a measurement of two energy-weighted gamma cascade angular distributions from polarized slow neutron capture on the Cl nucleus, one parity-odd correlation propor…
First Observation of -odd Asymmetry in Polarized Neutron Capture on Hydrogen
D. Blyth, J. Fry, N. Fomin +61
We report the first observation of the parity-violating 2.2 MeV gamma-ray asymmetry in neutron-proton capture using polarized cold neutrons incident on a liquid parahydr…
Bernstein Polynomials based Probabilistic Interpretation of Quark Hadron Duality
Evan Askanazi, Simonetta Liuti
It is now widely recognized that large Bjorken data play an important role in global analyses of Parton Distribution Functions (PDFs) even at collider energies, through perturb…
Exploring Nucleon Structure with the Self-Organizing Maps Algorithm
Evan M. Askanazi, Katherine A. Holcomb, Simonetta Liuti
We discuss the application of an alternative type of neural network, the Self-Organizing Map to extract parton distribution functions from various hard scattering processes.