Malachi Schram

<i>Colloquium</i>: Machine learning in nuclear physics

A. Boehnlein, Markus Diefenthaler, N. Sato et al. · Reviews of Modern Physics · 2022 · 211 citations · Full text

Physics with CEBAF at 12 GeV and future opportunities

J. Arrington, M. Battaglieri, A. Boehnlein et al. · Progress in Particle and Nuclear Physics · 2022 · 72 citations · Full text

Physics, Experimental Physics, Future Opportunities +5

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders

Majdi I. Radaideh, Chris H. Pappas, Jared Walden et al. · Digital Signal Processing · 2022 · 43 citations · Full text

Electrical Engineering, Anomaly Detection, Machine Learning +9

Tritium Beta Spectrum Measurement and Neutrino Mass Limit from Cyclotron Radiation Emission Spectroscopy

A. Ashtari Esfahani, S. Böser, N. Buzinsky et al. · Physical Review Letters · 2023 · 40 citations · Full text

Neutrino Mass Scale, Neutrino Property, Experimental Nuclear Physics +14

A.I. for nuclear physics

Paulo F. Bedaque, A. Boehnlein, M. Cromaz et al. · The European Physical Journal A · 2021 · 39 citations · Full text

Experimental Nuclear Physics, Nuclear Physics, Physics +6