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ORCIDGregor Kasieczka
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2020 – today
- 2025
[i24]Kristian Gonzalez Barman, Sascha Caron, Emily Sullivan, Henk W. de Regt, Roberto Ruiz de Austri, Mieke Boon, Michael Färber, Stefan Fröse
, Faegheh Hasibi, Andreas Ipp, Rukshak Kapoor, Gregor Kasieczka, Daniel Kostic, Michael Krämer, Tobias Golling, Luis G. Lopez, Jesus Marco, Sydney Otten, Pawel Pawlowski, Pietro Vischia, Erik Weber, Christoph Weniger:
Large Physics Models: Towards a collaborative approach with Large Language Models and Foundation Models. CoRR abs/2501.05382 (2025)- [i23]Joschka Birk, Frank Gaede, Anna Hallin, Gregor Kasieczka, Martina Mozzanica, Henning Rose:
OmniJet-αC: Learning point cloud calorimeter simulations using generative transformers. CoRR abs/2501.05534 (2025) - 2024
- [j6]Patrick Odagiu, Zhiqiang Que, Javier M. Duarte, Johannes Haller, Gregor Kasieczka, Artur Lobanov, Vladimir Loncar, Wayne Luk, Jennifer Ngadiuba, Maurizio Pierini, Philipp Rincke, Arpita Seksaria, Sioni Summers, Andre Sznajder, Alexander D. Tapper, Thea Klæboe Årrestad:
Ultrafast jet classification at the HL-LHC. Mach. Learn. Sci. Technol. 5(3): 35017 (2024) - [j5]Joschka Birk, Anna Hallin, Gregor Kasieczka:
OmniJet-α: the first cross-task foundation model for particle physics. Mach. Learn. Sci. Technol. 5(3): 35031 (2024) - [d1]Oz Amram, Luca Anzalone, Joschka Birk, Darius A. Faroughy, Anna Hallin, Gregor Kasieczka, Michael Krämer, Ian Pang, Humberto Reyes-González, David Shih:
Aspen Open Jets: a real-world ML-ready dataset for jet physics. UHH-FDR, 2024
- [i22]Patrick Odagiu, Zhiqiang Que, Javier M. Duarte, Johannes Haller, Gregor Kasieczka, Artur Lobanov, Vladimir Loncar, Wayne Luk, Jennifer Ngadiuba, Maurizio Pierini, Philipp Rincke, Arpita Seksaria, Sioni Summers, Andre Sznajder, Alexander D. Tapper, Thea Klæboe Årrestad:
Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC. CoRR abs/2402.01876 (2024) - [i21]Joschka Birk, Anna Hallin, Gregor Kasieczka:
OmniJet-α: The first cross-task foundation model for particle physics. CoRR abs/2403.05618 (2024) - [i20]Thorsten Buss, Frank Gaede, Gregor Kasieczka, Claudius Krause, David Shih:
Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows. CoRR abs/2405.20407 (2024) - [i19]Anna Hallin, Gregor Kasieczka, Sabine Kraml, André Lessa, Louis Moureaux, Tore von Schwartz, David Shih:
Universal New Physics Latent Space. CoRR abs/2407.20315 (2024) - [i18]Sebastian Bieringer, Sascha Diefenbacher, Gregor Kasieczka, Mathias Trabs:
Calibrating Bayesian Generative Machine Learning for Bayesiamplification. CoRR abs/2408.00838 (2024) - [i17]Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang:
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. CoRR abs/2410.21611 (2024) - [i16]Oz Amram, Luca Anzalone, Joschka Birk, Darius A. Faroughy, Anna Hallin, Gregor Kasieczka, Michael Krämer, Ian Pang, Humberto Reyes-González, David Shih:
Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics. CoRR abs/2412.10504 (2024) - [i15]Seth Nabat, Aishik Ghosh, Edmund Witkowski, Gregor Kasieczka, Daniel Whiteson:
Learning Broken Symmetries with Approximate Invariance. CoRR abs/2412.18773 (2024) - 2023
- [j4]Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, Katja Krüger, Peter McKeown, Lennart Rustige:
New angles on fast calorimeter shower simulation. Mach. Learn. Sci. Technol. 4(3): 35044 (2023) - [i14]Erik Buhmann, Gregor Kasieczka, Jesse Thaler:
EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets. CoRR abs/2301.08128 (2023) - [i13]Erik Buhmann, Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, William Korcari, Katja Krüger, Peter McKeown:
CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation. CoRR abs/2305.04847 (2023) - [i12]Erik Buhmann, Frank Gaede, Gregor Kasieczka, Anatolii Korol, William Korcari, Katja Krüger, Peter McKeown:
CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation. CoRR abs/2309.05704 (2023) - [i11]Erik Buhmann, Cedric Ewen, Darius A. Faroughy, Tobias Golling, Gregor Kasieczka, Matthew Leigh, Guillaume Quétant, John Andrew Raine, Debajyoti Sengupta, David Shih:
EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion. CoRR abs/2310.00049 (2023) - [i10]Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs:
Statistical guarantees for stochastic Metropolis-Hastings. CoRR abs/2310.09335 (2023) - [i9]Joschka Birk, Erik Buhmann, Cedric Ewen, Gregor Kasieczka, David Shih:
Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Information. CoRR abs/2312.00123 (2023) - [i8]Ranit Das, Gregor Kasieczka, David Shih:
Residual ANODE. CoRR abs/2312.11629 (2023) - [i7]Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs:
AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization. CoRR abs/2312.14027 (2023) - 2022
- [j3]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:
Shared Data and Algorithms for Deep Learning in Fundamental Physics. Comput. Softw. Big Sci. 6(1) (2022) - [j2]Erik Buhmann, Sascha Diefenbacher, Daniel Hundhausen, Gregor Kasieczka, William Korcari, Engin Eren, Frank Gaede, Katja Krüger, Peter McKeown, Lennart Rustige:
Hadrons, better, faster, stronger. Mach. Learn. Sci. Technol. 3(2): 25014 (2022) - [c1]Janis Kummer, Lennart Rustige, Florian Griese, Kerstin Borras, Marcus Brüggen, Patrick L. S. Connor, Frank Gaede, Gregor Kasieczka, Peter Schleper:
Radio Galaxy Classification with wGAN-Supported Augmentation. GI-Jahrestagung 2022: 469-478 - [i6]Andreas Adelmann, Walter Hopkins, Evangelos Kourlitis, Michael Kagan, Gregor Kasieczka, Claudius Krause, David Shih, Vinicius Mikuni, Benjamin Nachman, Kevin Pedro, Daniel Winklehner:
New directions for surrogate models and differentiable programming for High Energy Physics detector simulation. CoRR abs/2203.08806 (2022) - [i5]Gabriele Benelli, Thomas Y. Chen, Javier M. Duarte, Matthew Feickert, Matthew J. Graham, Lindsey Gray, Dan Hackett, Philip C. Harris, Shih-Chieh Hsu, Gregor Kasieczka, Elham E Khoda, Matthias Komm, Mia Liu, Mark S. Neubauer, Scarlet Norberg, Alexx Perloff, Marcel Rieger, Claire Savard, Kazuhiro Terao, Savannah Thais, Avik Roy, Jean-Roch Vlimant, Grigorios Chachamis:
Data Science and Machine Learning in Education. CoRR abs/2207.09060 (2022) - [i4]Ranit Das, Gregor Kasieczka, David Shih:
Feature Selection with Distance Correlation. CoRR abs/2212.00046 (2022) - 2021
- [b1]Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, Uwe Klemradt:
Deep Learning for Physics Research. WorldScientific 2021, ISBN 9789811237454, pp. 1-340 - [j1]Erik Buhmann, Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, Katja Krüger:
Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed. Comput. Softw. Big Sci. 5(1) (2021) - [i3]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:
Shared Data and Algorithms for Deep Learning in Fundamental Physics. CoRR abs/2107.00656 (2021) - [i2]Gregor Kasieczka, Benjamin Nachman, David Shih:
New Methods and Datasets for Group Anomaly Detection From Fundamental Physics. CoRR abs/2107.02821 (2021)
2010 – 2019
- 2019
- [i1]Marco Bellagente, Anja Butter, Gregor Kasieczka, Tilman Plehn, Ramon Winterhalder:
How to GAN away Detector Effects. CoRR abs/1912.00477 (2019)
Coauthor Index
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