Classification without labels: Learning from mixed samples in high energy physics

9 August 2017

Papers citing "Classification without labels: Learning from mixed samples in high energy physics"

23 / 23 papers shown

Title
CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation Debasish Sengupta Samuel Klein J. A. Raine T. Golling OOD 29 27 0 08 May 2023
Weakly-Supervised Anomaly Detection in the Milky Way M. Pettee Sowmya Thanvantri Benjamin Nachman David Shih M. Buckley J. Collins 21 7 0 05 May 2023
Anomalies, Representations, and Self-Supervision B. Dillon Luigi Favaro Friedrich Feiden Tanmoy Modak Tilman Plehn 39 9 0 11 Jan 2023
Resonant Anomaly Detection with Multiple Reference Datasets Mayee F. Chen Benjamin Nachman Frederic Sala 35 5 0 20 Dec 2022
Machine-Learned Exclusion Limits without Binning E. Arganda Andrés D. Pérez M. D. L. Rios Rosa María Sandá Seoane 43 9 0 09 Nov 2022
Machine Learning in the Search for New Fundamental Physics G. Karagiorgi Gregor Kasieczka S. Kravitz Benjamin Nachman David Shih AI4CE 49 113 0 07 Dec 2021
Towards a method to anticipate dark matter signals with deep learning at the LHC E. Arganda A. Medina A. D. Perez A. Szynkman 22 7 0 25 May 2021
Autoencoders for unsupervised anomaly detection in high energy physics Thorben Finke Michael Krämer A. Morandini A. Mück I. Oleksiyuk 31 83 0 19 Apr 2021
Comparing Weak- and Unsupervised Methods for Resonant Anomaly Detection J. Collins P. Martín-Ramiro Benjamin Nachman David Shih 34 44 0 05 Apr 2021
Bump Hunting in Latent Space Blaž Bortolato B. Dillon J. Kamenik Aleks Smolkovič DRL 39 43 0 11 Mar 2021
A Living Review of Machine Learning for Particle Physics Matthew Feickert Benjamin Nachman KELM AI4CE 39 178 0 02 Feb 2021
E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once Benjamin Nachman Jesse Thaler 37 33 0 18 Jan 2021
GPU coprocessors as a service for deep learning inference in high energy physics J. Krupa Kelvin Lin M. Acosta Flechas Jack T. Dinsmore Javier Mauricio Duarte ... K. Pedro D. Rankin Natchanon Suaysom Matthew Trahms N. Tran BDL 3DV 20 32 0 20 Jul 2020
Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review T. Dorigo P. D. Castro 32 14 0 17 Jul 2020
Machine Learning on data with sPlot background subtraction M. Borisyak N. Kazeev 21 11 0 28 May 2019
Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra A. Chakraborty Sung Hak Lim M. Nojiri 42 43 0 03 Apr 2019
ParticleNet: Jet Tagging via Particle Clouds H. Qu L. Gouskos 3DPC MU 30 229 0 22 Feb 2019
Energy Flow Networks: Deep Sets for Particle Jets Patrick T. Komiske E. Metodiev Jesse Thaler PINN 3DPC 45 251 0 11 Oct 2018
INFERNO: Inference-Aware Neural Optimisation P. D. Castro T. Dorigo 24 47 0 12 Jun 2018
Infrared Safety of a Neural-Net Top Tagging Algorithm Suyong Choi Seung J. Lee M. Perelstein 20 39 0 04 Jun 2018
Opening the black box of neural nets: case studies in stop/top discrimination Thomas Roxlo M. Reece 21 22 0 24 Apr 2018
On the Topic of Jets: Disentangling Quarks and Gluons at Colliders E. Metodiev Jesse Thaler 34 71 0 31 Jan 2018
QCD-Aware Recursive Neural Networks for Jet Physics Gilles Louppe Kyunghyun Cho C. Becot Kyle Cranmer BDL 24 189 0 02 Feb 2017