A Guide to Constraining Effective Field Theories with Machine Learning

30 April 2018

Papers citing "A Guide to Constraining Effective Field Theories with Machine Learning"

22 / 22 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 58 4 0 04 Apr 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
Data-driven Science and Machine Learning Methods in Laser-Plasma Physics Andreas Döpp C. Eberle S. Howard F. Irshad Jinpu Lin M. Streeter AI4CE 34 63 0 30 Nov 2022
Exploration of Parameter Spaces Assisted by Machine Learning A. Hammad Myeonghun Park Raymundo Ramos Pankaj Saha 26 15 0 20 Jul 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
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful Joeri Hermans Arnaud Delaunoy François Rozet Antoine Wehenkel Volodimir Begy Gilles Louppe 64 38 0 13 Oct 2021
A Cautionary Tale of Decorrelating Theory Uncertainties A. Ghosh Benjamin Nachman 35 17 0 16 Sep 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 32 14 0 17 Jul 2020
Bayesian Neural Networks for Fast SUSY Predictions B. Kronheim M. Kuchera Harrison B. Prosper A. Karbo 21 17 0 09 Jul 2020
Simulation Assisted Likelihood-free Anomaly Detection Anders Andreassen Benjamin Nachman David Shih 22 112 0 14 Jan 2020
How to GAN away Detector Effects Marco Bellagente A. Butter Gregor Kasieczka Tilman Plehn R. Winterhalder GAN 21 86 0 01 Dec 2019
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
Interpretable Deep Learning for Two-Prong Jet Classification with Jet Spectra A. Chakraborty Sung Hak Lim M. Nojiri 42 43 0 03 Apr 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 32 20 0 10 Mar 2019
Energy Flow Networks: Deep Sets for Particle Jets Patrick T. Komiske E. Metodiev Jesse Thaler PINN 3DPC 45 251 0 11 Oct 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank Wood 39 31 0 20 Jul 2018
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
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 60 358 0 18 May 2018
Constraining Effective Field Theories with Machine Learning Johann Brehmer Kyle Cranmer Gilles Louppe J. Pavez AI4CE 16 149 0 30 Apr 2018