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Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection

Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection

5 April 2021
J. Collins
P. Martín-Ramiro
Benjamin Nachman
David Shih
ArXivPDFHTML

Papers citing "Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection"

14 / 14 papers shown
Title
Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics
Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics
Sebastian Springer
Andre Scaffidi
Maximilian Autenrieth
Gabriella Contardo
Alessandro Laio
R. Trotta
H. Haario
42
0
0
31 Mar 2025
TRANSIT your events into a new mass: Fast background interpolation for weakly-supervised anomaly searches
Ivan Oleksiyuk
Slava Voloshynovskiy
Tobias Golling
DiffM
41
0
0
06 Mar 2025
Improving new physics searches with diffusion models for event
  observables and jet constituents
Improving new physics searches with diffusion models for event observables and jet constituents
Debajyoti Sengupta
Matthew Leigh
J. A. Raine
Samuel Klein
T. Golling
DiffM
46
15
0
15 Dec 2023
Improving the performance of weak supervision searches using transfer
  and meta-learning
Improving the performance of weak supervision searches using transfer and meta-learning
H. Beauchesne
Zong-En Chen
Cheng-Wei Chiang
20
8
0
11 Dec 2023
High-dimensional and Permutation Invariant Anomaly Detection
High-dimensional and Permutation Invariant Anomaly Detection
Vinicius Mikuni
Benjamin Nachman
DiffM
19
16
0
06 Jun 2023
IRC-safe Graph Autoencoder for unsupervised anomaly detection
IRC-safe Graph Autoencoder for unsupervised anomaly detection
Oliver Atkinson
Akanksha Bhardwaj
C. Englert
P. Konar
Vishal S. Ngairangbam
M. Spannowsky
21
26
0
26 Apr 2022
Machine Learning in the Search for New Fundamental Physics
Machine Learning in the Search for New Fundamental Physics
G. Karagiorgi
Gregor Kasieczka
S. Kravitz
Benjamin Nachman
David Shih
AI4CE
42
113
0
07 Dec 2021
Online-compatible Unsupervised Non-resonant Anomaly Detection
Online-compatible Unsupervised Non-resonant Anomaly Detection
Vinicius Mikuni
Benjamin Nachman
David Shih
25
35
0
11 Nov 2021
Challenges for Unsupervised Anomaly Detection in Particle Physics
Challenges for Unsupervised Anomaly Detection in Particle Physics
Katherine Fraser
S. Homiller
Rashmish K. Mishra
B. Ostdiek
M. Schwartz
DRL
27
43
0
13 Oct 2021
Autoencoders for unsupervised anomaly detection in high energy physics
Autoencoders for unsupervised anomaly detection in high energy physics
Thorben Finke
Michael Krämer
A. Morandini
A. Mück
I. Oleksiyuk
18
83
0
19 Apr 2021
Better Latent Spaces for Better Autoencoders
Better Latent Spaces for Better Autoencoders
B. Dillon
Tilman Plehn
C. Sauer
P. Sorrenson
BDL
DRL
19
55
0
16 Apr 2021
Bump Hunting in Latent Space
Bump Hunting in Latent Space
Blaž Bortolato
B. Dillon
J. Kamenik
Aleks Smolkovič
DRL
21
43
0
11 Mar 2021
Topological Obstructions to Autoencoding
Topological Obstructions to Autoencoding
Joshua D. Batson
C. G. Haaf
Yonatan Kahn
Daniel A. Roberts
AI4CE
34
37
0
16 Feb 2021
A Living Review of Machine Learning for Particle Physics
A Living Review of Machine Learning for Particle Physics
Matthew Feickert
Benjamin Nachman
KELM
AI4CE
24
176
0
02 Feb 2021
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