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2001.05486
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i-flow: High-dimensional Integration and Sampling with Normalizing Flows
15 January 2020
Christina Gao
J. Isaacson
Claudius Krause
AI4CE
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Papers citing
"i-flow: High-dimensional Integration and Sampling with Normalizing Flows"
11 / 11 papers shown
Title
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
Thorsten Buss
F. Gaede
Gregor Kasieczka
Claudius Krause
David Shih
AI4CE
30
6
0
30 May 2024
Unifying Simulation and Inference with Normalizing Flows
Haoxing Du
Claudius Krause
Vinicius Mikuni
Benjamin Nachman
Ian Pang
David Shih
36
3
0
29 Apr 2024
Improved off-policy training of diffusion samplers
Marcin Sendera
Minsu Kim
Sarthak Mittal
Pablo Lemos
Luca Scimeca
Jarrid Rector-Brooks
Alexandre Adam
Yoshua Bengio
Nikolay Malkin
OffRL
66
17
0
07 Feb 2024
Comparative Study of Coupling and Autoregressive Flows through Robust Statistical Tests
A. Coccaro
Marco Letizia
H. Reyes-González
Riccardo Torre
OOD
30
5
0
23 Feb 2023
Machine Learning in the Search for New Fundamental Physics
G. Karagiorgi
Gregor Kasieczka
S. Kravitz
Benjamin Nachman
David Shih
AI4CE
39
113
0
07 Dec 2021
Path Integral Sampler: a stochastic control approach for sampling
Qinsheng Zhang
Yongxin Chen
DiffM
15
101
0
30 Nov 2021
Optimising simulations for diphoton production at hadron colliders using amplitude neural networks
Joseph Aylett-Bullock
S. Badger
Ryan Moodie
11
22
0
17 Jun 2021
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows
Claudius Krause
David Shih
AI4CE
25
81
0
09 Jun 2021
Latent Space Refinement for Deep Generative Models
R. Winterhalder
Marco Bellagente
Benjamin Nachman
BDL
GAN
DRL
DiffM
10
27
0
01 Jun 2021
Neural Network-Based Approach to Phase Space Integration
Matthew D. Klimek
M. Perelstein
12
74
0
26 Oct 2018
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