M. S. Neubauer

1. Applications and Techniques for Fast Machine Learning in Science
   2021/10/25 by Allison McCarn Deiana, A. M. Deiana, Nhan Viet Tran +111 · 1 voice · 3 citations
   Decision Sciences · Computer Science · #Scientific Computing and Data Management #Neural Networks and Reservoir Computing #Anomaly Detection Techniques and Applications
2. Machine Learning in High Energy Physics Community White Paper
   2018/07/08 by Kim Albertsson, Piero Altoè, Albertsson, Kim +224 · 9 citations
   Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neutrino Physics Research #Particle Detector Development and Performance #Particle physics theoretical and experimental studies
3. Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks
   2025/01/10 by Ayush Khot, Khot, Ayush, Xiwei Wang +7 · 5 citations
   Computer Science · Engineering · #Aerodynamics and Acoustics in Jet Flows #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Machine Learning (cs.LG) #Nuclear Engineering Thermal-Hydraulics
4. Explainable AI for High Energy Physics
   2022/06/14 by M. S. Neubauer, Neubauer, Mark S., A. Roy +1 · 2 citations
   Computer Science · #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Physical sciences #Generative Adversarial Networks and Image Synthesis #High Energy Physics - Experiment (hep-ex) #Machine Learning (cs.LG)
5. Deep Learning for the Matrix Element Method
   2022/11/21 by M. Feickert, Feickert, Matthew, Mihir Katare +5 · 1 citation
   Physics and Astronomy · Materials Science · Engineering · #Particle Detector Development and Performance #Machine Learning in Materials Science #Nuclear reactor physics and engineering