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1901.05282
Cited By
LHC analysis-specific datasets with Generative Adversarial Networks
16 January 2019
B. Hashemi
N. Amin
Kaustuv Datta
D. Olivito
M. Pierini
GAN
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Papers citing
"LHC analysis-specific datasets with Generative Adversarial Networks"
31 / 31 papers shown
Forecasting Generative Amplification
Henning Bahl
Sascha Diefenbacher
Nina Elmer
Tilman Plehn
Jonas Spinner
212
2
0
09 Sep 2025
Extrapolating Jet Radiation with Autoregressive Transformers
A. Butter
François Charton
Javier Marino Villadamigo
Ayodele Ore
Tilman Plehn
Jonas Spinner
256
5
0
16 Dec 2024
A Lorentz-Equivariant Transformer for All of the LHC
Johann Brehmer
Victor Bresó
P. D. Haan
Tilman Plehn
Huilin Qu
Jonas Spinner
Jesse Thaler
BDL
354
52
0
01 Nov 2024
Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows
Thorsten Buss
F. Gaede
Gregor Kasieczka
Claudius Krause
David Shih
AI4CE
326
19
0
30 May 2024
Deep Generative Models for Detector Signature Simulation: A Taxonomic Review
Reviews in Physics (RP), 2023
Baran Hashemi
Claudius Krause
360
30
0
15 Dec 2023
Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Information
Joschka Birk
E. Buhmann
Cedric Ewen
Gregor Kasieczka
David Shih
409
14
0
30 Nov 2023
Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data
Yi Huang
Zhongjing Jiang
Shinjae Yoo
Jin-zhi Huang
127
5
0
23 Oct 2023
EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion
E. Buhmann
Cedric Ewen
D. Faroughy
J. A. Raine
Gregor Kasieczka
Matthew Leigh
Guillaume Quétant
C. Pollard
Debajyoti Sengupta
David Shih
DiffM
282
33
0
29 Sep 2023
CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation
Journal of Instrumentation (JINST), 2023
E. Buhmann
F. Gaede
Gregor Kasieczka
A. Korol
W. Korcari
K. Krüger
Peter McKeown
DiffM
265
36
0
11 Sep 2023
PC-Droid: Faster diffusion and improved quality for particle cloud generation
Matthew Leigh
Debasish Sengupta
C. Pollard
Guillaume Quétant
J. A. Raine
DiffM
280
14
0
13 Jul 2023
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
SciPost Physics (SciPost Phys.), 2023
Matthew Leigh
Debasish Sengupta
Guillaume Quétant
C. Pollard
K. Zoch
J. A. Raine
DiffM
237
51
0
09 Mar 2023
Evaluating generative models in high energy physics
Raghav Kansal
Anni Li
Javier Mauricio Duarte
N. Chernyavskaya
M. Pierini
B. Orzari
T. Tomei
MedIm
251
45
0
18 Nov 2022
Explainable AI for High Energy Physics
Mark S. Neubauer
Avik Roy
168
13
0
14 Jun 2022
Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders
M. Touranakou
N. Chernyavskaya
Javier Mauricio Duarte
Dimitrios Gunopulos
Raghav Kansal
B. Orzari
M. Pierini
T. Tomei
J. Vlimant
151
20
0
01 Mar 2022
Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder
International Conference on Machine Learning and Applications (ICMLA), 2021
Yi Huang
Zhongjing Jiang
Shinjae Yoo
Jin-zhi Huang
110
11
0
09 Nov 2021
Generative Networks for Precision Enthusiasts
SciPost Physics (SciPost Phys.), 2021
A. Butter
Theo Heimel
Sander Hummerich
Tobias Krebs
Tilman Plehn
Armand Rousselot
Sophia Vent
AI4CE
305
65
0
22 Oct 2021
Optimising simulations for diphoton production at hadron colliders using amplitude neural networks
Journal of High Energy Physics (JHEP), 2021
Joseph Aylett-Bullock
S. Badger
Ryan Moodie
305
34
0
17 Jun 2021
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows
Claudius Krause
David Shih
AI4CE
370
91
0
09 Jun 2021
Latent Space Refinement for Deep Generative Models
R. Winterhalder
Marco Bellagente
Benjamin Nachman
BDL
GAN
DRL
DiffM
341
28
0
01 Jun 2021
The use of Generative Adversarial Networks to characterise new physics in multi-lepton final states at the LHC
Thabang Lebese
X. Ruan
GAN
178
9
0
31 May 2021
Understanding Event-Generation Networks via Uncertainties
SciPost Physics (SciPost Phys.), 2021
Marco Bellagente
Manuel Haussmann
Michel Luchmann
Tilman Plehn
BDL
224
62
0
09 Apr 2021
A Living Review of Machine Learning for Particle Physics
Matthew Feickert
Benjamin Nachman
KELM
AI4CE
210
216
0
02 Feb 2021
Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics
Raghav Kansal
Javier Mauricio Duarte
B. Orzari
T. Tomei
M. Pierini
M. Touranakou
J. Vlimant
Dimitrios Gunopoulos
GAN
217
24
0
30 Nov 2020
Parameter Estimation using Neural Networks in the Presence of Detector Effects
Anders Andreassen
S. Hsu
Benjamin Nachman
Natchanon Suaysom
Adithya Suresh
349
15
0
07 Oct 2020
Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning
Cheng Chen
O. Cerri
Thong Q. Nguyen
J. Vlimant
M. Pierini
98
10
0
05 Oct 2020
DCTRGAN: Improving the Precision of Generative Models with Reweighting
Journal of Instrumentation (JINST), 2020
Yuan-Tang Chou
E. Eren
Gregor Kasieczka
A. Korol
Benjamin Nachman
David Shih
173
48
0
03 Sep 2020
GANplifying Event Samples
A. Butter
Yuan-Tang Chou
Gregor Kasieczka
Benjamin Nachman
Tilman Plehn
GAN
311
83
0
14 Aug 2020
Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN)
International Joint Conference on Artificial Intelligence (IJCAI), 2020
Yasir Alanazi
Nobuo Sato
Tianbo Liu
W. Melnitchouk
P. Ambrozewicz
...
E. Pritchard
M. Robertson
R. Strauss
L. Velasco
Yaohang Li
GAN
400
71
0
29 Jan 2020
i-flow: High-dimensional Integration and Sampling with Normalizing Flows
Christina Gao
J. Isaacson
Claudius Krause
AI4CE
233
128
0
15 Jan 2020
Anomaly Detection with Density Estimation
Benjamin Nachman
David Shih
204
238
0
14 Jan 2020
How to GAN away Detector Effects
SciPost Physics (SciPost Phys.), 2019
Marco Bellagente
A. Butter
Gregor Kasieczka
Tilman Plehn
R. Winterhalder
GAN
533
100
0
01 Dec 2019
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