SciPost: Topic details

Machine learning (ML)

Publications

Scaling laws in jet classification
by Joshua Batson, Yonatan Kahn,
SciPost Phys. Core 8, 034 (2025)
Identifying quantum phase transitions with minimal prior knowledge by unsupervised learning
by Mohamad Ali Marashli, Ho Lai Henry Lam, Hamam Mokayed, Fredrik Sandin, Marcus Liwicki, Ho-Kin Tang, Wing Chi Yu,
SciPost Phys. Core 8, 029 (2025)
The landscape of unfolding with machine learning
by Nathan Huetsch, Javier Mariño Villadamigo, Alexander Shmakov, Sascha Diefenbacher, Vinicius Mikuni, Theo Heimel, Michael Fenton, Kevin Greif, Benjamin Nachman, Daniel Whiteson, Anja Butter, Tilman Plehn,
SciPost Phys. 18, 070 (2025)
Learning the simplicity of scattering amplitudes
by Clifford Cheung, Aurélien Dersy, Matthew D. Schwartz,
SciPost Phys. 18, 040 (2025)
Learning lattice quantum field theories with equivariant continuous flows
by Mathis Gerdes, Pim de Haan, Corrado Rainone, Roberto Bondesan, Miranda C. N. Cheng,
SciPost Phys. 15, 238 (2023)
Exploring unsupervised top tagging using Bayesian inference
by Ezequiel Alvarez, Manuel Szewc, Alejandro Szynkman, Santiago A. Tanco, Tatiana Tarutina,
SciPost Phys. Core 6, 046 (2023)
Loop amplitudes from precision networks
by Simon Badger, Anja Butter, Michel Luchmann, Sebastian Pitz, Tilman Plehn,
SciPost Phys. Core 6, 034 (2023)
Machine learning and LHC event generation
by Anja Butter, Tilman Plehn, Steffen Schumann, Simon Badger, Sascha Caron, Kyle Cranmer, Francesco Armando Di Bello, Etienne Dreyer, Stefano Forte, Sanmay Ganguly, Dorival Gonçalves, Eilam Gross, Theo Heimel, Gudrun Heinrich, Lukas Heinrich, Alexander Held, Stefan Höche, Jessica N. Howard, Philip Ilten, Joshua Isaacson, Timo Janßen, Stephen Jones, Marumi Kado, Michael Kagan, Gregor Kasieczka, Felix Kling, Sabine Kraml, Claudius Krause, Frank Krauss, Kevin Kröninger, Rahool Kumar Barman, Michel Luchmann, Vitaly Magerya, Daniel Maitre, Bogdan Malaescu, Fabio Maltoni, Till Martini, Olivier Mattelaer, Benjamin Nachman, Sebastian Pitz, Juan Rojo, Matthew Schwartz, David Shih, Frank Siegert, Roy Stegeman, Bob Stienen, Jesse Thaler, Rob Verheyen, Daniel Whiteson, Ramon Winterhalder, Jure Zupan,
SciPost Phys. 14, 079 (2023)
Real-time discrimination of photon pairs using machine learning at the LHC
by Sean Benson, Adrián Casais Vidal, Xabier Cid Vidal, Albert Puig Navarro,
SciPost Phys. 7, 062 (2019)
Investigating ultrafast quantum magnetism with machine learning
by Giammarco Fabiani, Johan H. Mentink,
SciPost Phys. 7, 004 (2019)
Quark-gluon tagging: Machine learning vs detector
by Gregor Kasieczka, Nicholas Kiefer, Tilman Plehn, Jennifer M. Thompson,
SciPost Phys. 6, 069 (2019)
Deep-learned Top Tagging with a Lorentz Layer
by Anja Butter, Gregor Kasieczka, Tilman Plehn, Michael Russell,
SciPost Phys. 5, 028 (2018)

Submissions (unpublished only)

Systematically Constructing the Likelihood for Boosted $H\to gg$ Decays
by Andrew J. Larkoski
(submitted 2025-03-24 to SciPost Physics)
Physics-informed neural networks viewpoint for solving the Dyson-Schwinger equations of quantum electrodynamics
by Rodrigo Carmo Terin
(submitted 2025-03-18 to SciPost Physics)
Encoding off-shell effects in top pair production in Direct Diffusion networks
by Mathias Kuschick
(submitted 2025-03-14 to SciPost Physics Proceedings)
MACK: Mismodeling Addressed with Contrastive Knowledge
by Liam Rankin Sheldon, Dylan Sheldon Rankin, Philip Harris
(submitted 2025-03-05 to SciPost Physics)
Interpolating amplitudes
by Víctor Bresó-Pla, Gudrun Heinrich, Vitaly Magerya, Anton Olsson
(submitted 2025-02-25 to SciPost Physics)
Learning Selection Cuts With Gradients
by Mike Hance, Juan Robles
(submitted 2025-02-14 to SciPost Physics Core)
Simplified derivations for high-dimensional convex learning problems
by David G. Clark, Haim Sompolinsky
(submitted 2025-02-11 to SciPost Physics Lecture Notes)
Super-Resolving Normalising Flows for Lattice Field Theories
by Marc Bauer, Renzo Kapust, Jan Martin Pawlowski, Finn Leon Temmen
(submitted 2025-02-08 to SciPost Physics)
How to Unfold Top Decays
by Luigi Favaro, Roman Kogler, Alexander Paasch, Sofia Palacios Schweitzer, Tilman Plehn, Dennis Schwarz
(submitted 2025-02-06 to SciPost Physics)
Advancing Tools for Simulation-Based Inference
by Henning Bahl, Victor Bresó, Giovanni De Crescenzo, Tilman Plehn
(submitted 2025-01-17 to SciPost Physics)
Generative Unfolding with Distribution Mapping
by Anja Butter, Sascha Diefenbacher, Nathan Huetsch, Vinicius Mikuni, Benjamin Nachman, Sofia Palacios Schweitzer, Tilman Plehn
(submitted 2025-01-07 to SciPost Physics)
Extrapolating Jet Radiation with Autoregressive Transformers
by Anja Butter, François Charton, Javier Mariño Villadamigo, Ayodele Ore, Tilman Plehn, Jonas Spinner
(submitted 2024-12-31 to SciPost Physics)
Precision calibration of calorimeter signals in the ATLAS experiment using an uncertainty-aware neural network
by ATLAS Collaboration
(submitted 2024-12-16 to SciPost Physics)
Transformer Neural Networks in the Measurement of $t\bar{t}H$ Production in the $H\,{\to}\,b\bar{b}$ Decay Channel with ATLAS
by Chris Scheulen on behalf of the ATLAS Collaboration
(submitted 2024-12-12 to SciPost Physics Proceedings)
Neutrino Classification Through Deep Learning
by María Fernanda Romo-Fuentes, Luis Eduardo Falcón-Morales
(submitted 2024-10-31 to SciPost Physics Proceedings)
Predicting Nuclear Binding Energy Using Generalized Additive Model
by Kristiyan Laoli
(submitted 2024-10-14 to SciPost Physics)

Top experts

Machine learning (ML)