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Gregor Kasieczka

EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets

Jan 17, 2023
Erik Buhmann, Gregor Kasieczka, Jesse Thaler

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* 18 pages, 8 figures, 2 tables

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Feature Selection with Distance Correlation

Nov 30, 2022
Ranit Das, Gregor Kasieczka, David Shih

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* 14 pages, 8 figures, 3 tables

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Machine Learning in the Search for New Fundamental Physics

Dec 07, 2021
Georgia Karagiorgi, Gregor Kasieczka, Scott Kravitz, Benjamin Nachman, David Shih

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* Preprint of article submitted to Nature Reviews Physics, 19 pages, 1 figure

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New Methods and Datasets for Group Anomaly Detection From Fundamental Physics

Jul 06, 2021
Gregor Kasieczka, Benjamin Nachman, David Shih

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* Accepted for ANDEA (Anomaly and Novelty Detection, Explanation and Accommodation) Workshop at KDD 2021

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Shared Data and Algorithms for Deep Learning in Fundamental Physics

Jul 01, 2021
Lisa Benato, Erik Buhmann, Martin Erdmann, Peter Fackeldey, Jonas Glombitza, Nikolai Hartmann, Gregor Kasieczka, William Korcari, Thomas Kuhr, Jan Steinheimer, Horst Stöcker, Tilman Plehn, Kai Zhou

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* 13 pages, 5 figures, 5 tables

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GANplifying Event Samples

Sep 16, 2020
Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, Benjamin Nachman, Tilman Plehn

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* 14 pages, 7 figures, fixed two equations, extended acknowledgments

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DCTRGAN: Improving the Precision of Generative Models with Reweighting

Sep 03, 2020
Sascha Diefenbacher, Engin Eren, Gregor Kasieczka, Anatolii Korol, Benjamin Nachman, David Shih

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* 14 pages, 8 figures

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