:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Matchev, Konstantin T., Matcheva, Katia, Ramond, Pierre, Verner, Sarunas
Format:	Preprint
Published:	2024
Subjects:	High Energy Physics - Phenomenology Machine Learning
Online Access:	https://arxiv.org/abs/2401.11513
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Electroweak Sphaleron Revisited: II. Study of Decay Dynamics
by: Matchev, Konstantin T., et al.
Published: (2025)

The Electroweak Sphaleron Revisited: I. Static Solutions, Energy Barrier, and Unstable Modes
by: Matchev, Konstantin T., et al.
Published: (2025)

Lie-Equivariant Quantum Graph Neural Networks
by: Neto, Jogi Suda, et al.
Published: (2024)

$M_{TN}$ is all you need: production of multiple semi-invisible resonances at hadron colliders
by: Dong, Zhongtian, et al.
Published: (2024)

Quantum Attention for Vision Transformers in High Energy Physics
by: Tesi, Alessandro, et al.
Published: (2024)

AI Agents for Variational Quantum Circuit Design
by: Knipfer, Marco, et al.
Published: (2026)

Quantum Diffusion Model for Quark and Gluon Jet Generation
by: Baidachna, Mariia, et al.
Published: (2024)

The Pareto Frontiers of Magic and Entanglement: The Case of Two Qubits
by: Roman, Alexander, et al.
Published: (2026)

Gravitational Production of Massive Spin-2 Particles During Reheating
by: Verner, Sarunas
Published: (2025)

$\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
by: Dong, Zhongtian, et al.
Published: (2023)

A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
by: Forestano, Roy T., et al.
Published: (2023)

Nonminimal Superheavy Dark Matter
by: Verner, Sarunas
Published: (2024)

The Landscape of Unfolding with Machine Learning
by: Huetsch, Nathan, et al.
Published: (2024)

Cosmological Collider Signatures of Higgs-$R^2$ Inflation
by: Ema, Yohei, et al.
Published: (2023)

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
by: Unlu, Eyup B., et al.
Published: (2024)

Gravitational Production of Heavy Particles during and after Inflation
by: Racco, Davide, et al.
Published: (2024)

Quantum Vision Transformers for Quark-Gluon Classification
by: Cara, Marçal Comajoan, et al.
Published: (2024)

Astrometric Detection of Ultralight Dark Matter
by: Dror, Jeff A., et al.
Published: (2024)

A New Window into Gravitationally Produced Scalar Dark Matter
by: Garcia, Marcos A. G., et al.
Published: (2023)

Truth, beauty, and goodness in grand unification: a machine learning approach
by: Kawai, Shinsuke, et al.
Published: (2024)

A Quantum Algorithm for Model-Independent Searches for New Physics
by: Matchev, Konstantin T., et al.
Published: (2020)

Gravitational Production of Spin-3/2 Particles During Reheating
by: Kaneta, Kunio, et al.
Published: (2023)

Gravitational Waves from Isocurvature Perturbations of Spectator Scalar Fields
by: Garcia, Marcos A. G., et al.
Published: (2025)

Gravitational Waves from Spectator Scalar Fields
by: Garcia, Marcos A. G., et al.
Published: (2025)

TASI Lectures on Physics for Machine Learning
by: Halverson, Jim
Published: (2024)

Inflaton decay in No-Scale Supergravity and Starobinsky-like models
by: Ema, Yohei, et al.
Published: (2024)

Scalar Field Fluctuations and the Production of Dark Matter
by: Garcia, Marcos A. G., et al.
Published: (2025)

A Perspective on Symbolic Machine Learning in Physical Sciences
by: Makke, Nour, et al.
Published: (2025)

Comparing Generative Models with the New Physics Learning Machine
by: Grossi, Samuele, et al.
Published: (2025)

Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC
by: Arganda, Ernesto, et al.
Published: (2024)

Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning
by: von Hippel, Matt, et al.
Published: (2025)

Exploration of Parameter Spaces Assisted by Machine Learning
by: Hammad, A., et al.
Published: (2022)

Constraints on Attractor Models of Inflation and Reheating from Planck, BICEP/Keck, ACT DR6, and SPT-3G Data
by: Ellis, John, et al.
Published: (2025)

Lecture notes on Machine Learning applications for global fits
by: Alda, Jorge
Published: (2026)

Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics
by: Menzo, Tony, et al.
Published: (2026)

Inflaton Production of Scalar Dark Matter through Fluctuations and Scattering
by: Choi, Gongjun, et al.
Published: (2024)

Moments of Clarity: Streamlining Latent Spaces in Machine Learning using Moment Pooling
by: Gambhir, Rikab, et al.
Published: (2024)

Advancing Physics Data Analysis through Machine Learning and Physics-Informed Neural Networks
by: Vatellis, Vasileios
Published: (2024)

Machine Learning Neutrino-Nucleus Cross Sections
by: Hackett, Daniel C., et al.
Published: (2024)

Exploring the flavor structure of quarks and leptons with reinforcement learning
by: Nishimura, Satsuki, et al.
Published: (2023)