Gregor Kasieczka

According to our database, Gregor Kasieczka authored at least 24 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Calibrating Bayesian Generative Machine Learning for Bayesiamplification.

Sebastian Bieringer, Sascha Diefenbacher, Gregor Kasieczka, Mathias Trabs

CoRR, 2024

Universal New Physics Latent Space.

Anna Hallin, Gregor Kasieczka, Sabine Kraml, André Lessa, Louis Moureaux, Tore von Schwartz, David Shih

CoRR, 2024

Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows.

Thorsten Buss, Frank Gaede, Gregor Kasieczka, Claudius Krause, David Shih

CoRR, 2024

OmniJet-α: The first cross-task foundation model for particle physics.

Joschka Birk, Anna Hallin, Gregor Kasieczka

CoRR, 2024

Sets are all you need: Ultrafast jet classification on FPGAs for HL-LHC.

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

CoRR, 2024

2023

New angles on fast calorimeter shower simulation.

Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, Katja Krüger, Peter McKeown, Lennart Rustige

Mach. Learn. Sci. Technol., September, 2023

AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization.

Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs

CoRR, 2023

Residual ANODE.

Ranit Das, Gregor Kasieczka, David Shih

CoRR, 2023

Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Information.

Joschka Birk, Erik Buhmann, Cedric Ewen, Gregor Kasieczka, David Shih

CoRR, 2023

Statistical guarantees for stochastic Metropolis-Hastings.

Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs

CoRR, 2023

EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion.

Erik Buhmann, Cedric Ewen, Darius A. Faroughy, Tobias Golling, Gregor Kasieczka, Matthew Leigh, Guillaume Quétant, John Andrew Raine, Debajyoti Sengupta, David Shih

CoRR, 2023

CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation.

Erik Buhmann, Frank Gaede, Gregor Kasieczka, Anatolii Korol, William Korcari, Katja Krüger, Peter McKeown

CoRR, 2023

CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation.

Erik Buhmann, Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, William Korcari, Katja Krüger, Peter McKeown

CoRR, 2023

EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets.

Erik Buhmann, Gregor Kasieczka, Jesse Thaler

CoRR, 2023

2022

Shared Data and Algorithms for Deep Learning in Fundamental Physics.

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

Comput. Softw. Big Sci., December, 2022

Hadrons, better, faster, stronger.

Erik Buhmann, Sascha Diefenbacher, Daniel Hundhausen, Gregor Kasieczka, William Korcari, Engin Eren, Frank Gaede, Katja Krüger, Peter McKeown, Lennart Rustige

Mach. Learn. Sci. Technol., 2022

Feature Selection with Distance Correlation.

Ranit Das, Gregor Kasieczka, David Shih

CoRR, 2022

Data Science and Machine Learning in Education.

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

CoRR, 2022

New directions for surrogate models and differentiable programming for High Energy Physics detector simulation.

Andreas Adelmann, Walter Hopkins, Evangelos Kourlitis, Michael Kagan, Gregor Kasieczka, Claudius Krause, David Shih, Vinicius Mikuni, Benjamin Nachman, Kevin Pedro, Daniel Winklehner

CoRR, 2022

Radio Galaxy Classification with wGAN-Supported Augmentation.

Janis Kummer, Lennart Rustige, Florian Griese, Kerstin Borras, Marcus Brüggen, Patrick L. S. Connor, Frank Gaede, Gregor Kasieczka, Peter Schleper

Proceedings of the 52. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2022, Informatik in den Naturwissenschaften, 26., 2022

2021

Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed.

Erik Buhmann, Sascha Diefenbacher, Engin Eren, Frank Gaede, Gregor Kasieczka, Anatolii Korol, Katja Krüger

Comput. Softw. Big Sci., 2021

New Methods and Datasets for Group Anomaly Detection From Fundamental Physics.

Gregor Kasieczka, Benjamin Nachman, David Shih

CoRR, 2021

Deep Learning for Physics Research

Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, Uwe Klemradt

WorldScientific, ISBN: 9789811285325, 2021

2019

How to GAN away Detector Effects.

Marco Bellagente, Anja Butter, Gregor Kasieczka, Tilman Plehn, Ramon Winterhalder

CoRR, 2019