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E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once

E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once

18 January 2021
Benjamin Nachman
Jesse Thaler
ArXivPDFHTML

Papers citing "E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once"

8 / 8 papers shown
Title
Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning
Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning
Sanghwan Bae
Jiwoo Hong
Min Young Lee
Hanbyul Kim
Jeongyeon Nam
Donghyun Kwak
OffRL
LRM
53
3
0
04 Apr 2025
Discriminative versus Generative Approaches to Simulation-based Inference
Benjamin Sluijter
S. Diefenbacher
W. Bhimji
Benjamin Nachman
46
0
0
11 Mar 2025
Resonant Anomaly Detection with Multiple Reference Datasets
Resonant Anomaly Detection with Multiple Reference Datasets
Mayee F. Chen
Benjamin Nachman
Frederic Sala
25
5
0
20 Dec 2022
Machine-Learned Exclusion Limits without Binning
Machine-Learned Exclusion Limits without Binning
E. Arganda
Andrés D. Pérez
M. D. L. Rios
Rosa María Sandá Seoane
30
9
0
09 Nov 2022
Bias and Priors in Machine Learning Calibrations for High Energy Physics
Bias and Priors in Machine Learning Calibrations for High Energy Physics
Rikab Gambhir
Benjamin Nachman
Jesse Thaler
AI4CE
22
7
0
10 May 2022
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with
  Normalizing Flows
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows
Claudius Krause
David Shih
AI4CE
28
81
0
09 Jun 2021
Latent Space Refinement for Deep Generative Models
Latent Space Refinement for Deep Generative Models
R. Winterhalder
Marco Bellagente
Benjamin Nachman
BDL
GAN
DRL
DiffM
10
27
0
01 Jun 2021
Towards a method to anticipate dark matter signals with deep learning at
  the LHC
Towards a method to anticipate dark matter signals with deep learning at the LHC
E. Arganda
A. Medina
A. D. Perez
A. Szynkman
14
7
0
25 May 2021
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