Parameterized Machine Learning for High-Energy Physics

28 January 2016

Papers citing "Parameterized Machine Learning for High-Energy Physics"

24 / 24 papers shown

Title
Contrastive Normalizing Flows for Uncertainty-Aware Parameter Estimation Ibrahim Elsharkawy Yonatan Kahn 21 0 0 13 May 2025
Discriminative versus Generative Approaches to Simulation-based Inference Benjamin Sluijter S. Diefenbacher W. Bhimji Benjamin Nachman 51 0 0 11 Mar 2025
FAIR Universe HiggsML Uncertainty Challenge Competition W. Bhimji P. Calafiura Ragansu Chakkappai Yuan-Tang Chou S. Diefenbacher ... D. Rousseau Benjamin Sluijter Benjamin Thorne Ihsan Ullah Yulei Zhang 46 2 0 03 Oct 2024
Improving Parametric Neural Networks for High-Energy Physics (and Beyond) Luca Anzalone T. Diotalevi D. Bonacorsi 32 3 0 01 Feb 2022
Autoencoders for Semivisible Jet Detection F. Canelli A. de Cosa L. Le Pottier J. Niedziela K. Pedro M. Pierini 27 33 0 06 Dec 2021
A Cautionary Tale of Decorrelating Theory Uncertainties A. Ghosh Benjamin Nachman 30 17 0 16 Sep 2021
Deconvolution-and-convolution Networks Yimin Yang Wandong Zhang Jonathan Wu Will Zhao Ao Chen 21 8 0 22 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
Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review T. Dorigo P. D. Castro 18 14 0 17 Jul 2020
General Framework for Binary Classification on Top Samples Lukáš Adam V. Mácha Václav Smídl Tomás Pevný 29 5 0 25 Feb 2020
Simulation Assisted Likelihood-free Anomaly Detection Anders Andreassen Benjamin Nachman David Shih 14 112 0 14 Jan 2020
MadMiner: Machine learning-based inference for particle physics Johann Brehmer F. Kling Irina Espejo Kyle Cranmer 21 113 0 24 Jul 2019
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 23 14 0 04 Jun 2019
CrossTrainer: Practical Domain Adaptation with Loss Reweighting Justin Chen Edward Gan Kexin Rong S. Suri Peter Bailis 22 4 0 07 May 2019
INFERNO: Inference-Aware Neural Optimisation P. D. Castro T. Dorigo 24 47 0 12 Jun 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 38 181 0 30 May 2018
A Guide to Constraining Effective Field Theories with Machine Learning Johann Brehmer Kyle Cranmer Gilles Louppe J. Pavez 9 138 0 30 Apr 2018
Constraining Effective Field Theories with Machine Learning Johann Brehmer Kyle Cranmer Gilles Louppe J. Pavez AI4CE 11 149 0 30 Apr 2018
Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation M. Scutari C. Vitolo A. Tucker 29 99 0 22 Apr 2018
Extremely Fast Decision Tree Chaitanya Manapragada Geoffrey I. Webb Mahsa Salehi 11 143 0 24 Feb 2018
Binarsity: a penalization for one-hot encoded features in linear supervised learning Mokhtar Z. Alaya Simon Bussy Stéphane Gaïffas Agathe Guilloux 34 30 0 24 Mar 2017
Decorrelated Jet Substructure Tagging using Adversarial Neural Networks C. Shimmin Peter Sadowski Pierre Baldi E. Weik D. Whiteson Edward Goul A. Søgaard GAN 25 114 0 10 Mar 2017
Multiple Instance Learning: A Survey of Problem Characteristics and Applications M. Carbonneau Dovile Juodelyte Eric Granger G. Gagnon 23 614 0 11 Dec 2016