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Neural Network-Based Approach to Phase Space Integration

Neural Network-Based Approach to Phase Space Integration

26 October 2018
Matthew D. Klimek
M. Perelstein
ArXivPDFHTML

Papers citing "Neural Network-Based Approach to Phase Space Integration"

5 / 5 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
0
0
04 Apr 2025
Convolutional L2LFlows: Generating Accurate Showers in Highly Granular
  Calorimeters Using Convolutional Normalizing Flows
Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows
Thorsten Buss
F. Gaede
Gregor Kasieczka
Claudius Krause
David Shih
AI4CE
36
6
0
30 May 2024
Bayesian Modelling of Multivalued Power Curves from an Operational Wind
  Farm
Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm
L. Bull
P. Gardner
T. Rogers
N. Dervilis
E. Cross
E. Papatheou
A. E. Maguire
C. Campos
K. Worden
11
12
0
30 Nov 2021
Optimising simulations for diphoton production at hadron colliders using
  amplitude neural networks
Optimising simulations for diphoton production at hadron colliders using amplitude neural networks
Joseph Aylett-Bullock
S. Badger
Ryan Moodie
13
22
0
17 Jun 2021
How to GAN away Detector Effects
How to GAN away Detector Effects
Marco Bellagente
A. Butter
Gregor Kasieczka
Tilman Plehn
R. Winterhalder
GAN
11
86
0
01 Dec 2019
1