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High Energy Physics Calorimeter Detector Simulation Using Generative Adversarial Networks With Domain Related Constraints.

, , , and . IEEE Access, (2021)

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Particle Detector Simulation using Generative Adversarial Networks with Domain Related Constraints., , , and . ICMLA, page 28-33. IEEE, (2019)Three Dimensional Energy Parametrized Generative Adversarial Networks for Electromagnetic Shower Simulation., , and . ICIP, page 3913-3917. IEEE, (2018)Stochastic performance tuning of complex simulation applications using unsupervised machine learning., and . SSCI, page 1-8. IEEE, (2016)Summary of the ACAT Round Table Discussion: Open-source, knowledge sharing and scientific collaboration, , and . Journal of Physics: Conference Series, (Jul 2, 2014)Machine Learning in High Energy Physics Community White Paper., , , , , , , , , and 108 other author(s). CoRR, (2018)Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors., , , and . CoRR, (2021)Distributed Training of Generative Adversarial Networks for Fast Detector Simulation., , , , , , and . ISC Workshops, volume 11203 of Lecture Notes in Computer Science, page 487-503. Springer, (2018)The Virtual Monte Carlo, , , , , , , , , and . CoRR, (2003)Identifying composite crosscutting concerns through semi-supervised learning., , , , , and . Softw. Pract. Exp., 44 (12): 1525-1545 (2014)Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics., , , , , , , , , and 6 other author(s). CoRR, (2019)