Cover Image

Stable and Interpretable Jet Physics with IRC-Safe Equivariant Feature Extraction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Konar, Partha, Ngairangbam, Vishal S., Spannowsky, Michael, Srivastava, Deepanshu
Format:	Preprint
Published:	2025
Subjects:	High Energy Physics - Phenomenology Machine Learning High Energy Physics - Experiment
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hypergraphs in LHC Phenomenology -- The Next Frontier of IRC-Safe Feature Extraction
by: Konar, Partha, et al.
Published: (2023)

From Reachability to Learnability: Geometric Design Principles for Quantum Neural Networks
by: Ngairangbam, Vishal S., et al.
Published: (2026)

Equivariant, Safe and Sensitive -- Graph Networks for New Physics
by: Bhardwaj, Akanksha, et al.
Published: (2024)

Optimal Equivariant Architectures from the Symmetries of Matrix-Element Likelihoods
by: Maître, Daniel, et al.
Published: (2024)

Enhancing anomaly detection with topology-aware autoencoders
by: Ngairangbam, Vishal S., et al.
Published: (2025)

Improved Ground State Estimation in Quantum Field Theories via Normalising Flow-Assisted Neural Quantum States
by: Ngairangbam, Vishal S., et al.
Published: (2025)

Interpretable deep learning models for the inference and classification of LHC data
by: Ngairangbam, Vishal S., et al.
Published: (2023)

Foundations of automatic feature extraction at LHC--point clouds and graphs
by: Bhardwaj, Akanksha, et al.
Published: (2024)

From Information Geometry to Jet Substructure: A Triality of Cumulant Tensors, Energy Correlators, and Hypergraphs
by: Bal, Aritra, et al.
Published: (2026)

Dissecting Jet-Tagger Through Mechanistic Interpretability
by: Rai, Saurabh, et al.
Published: (2026)

Precise probing of the inert Higgs-doublet model at the LHC
by: Ghosh, Anupam, et al.
Published: (2021)

Explainable Equivariant Neural Networks for Particle Physics: PELICAN
by: Bogatskiy, Alexander, et al.
Published: (2023)

E-PCN: Jet Tagging with Explainable Particle Chebyshev Networks Using Kinematic Features
by: Islam, Md Raqibul, et al.
Published: (2025)

Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics
by: Amram, Oz, et al.
Published: (2024)

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane
by: Patel, Pahal D., et al.
Published: (2026)

Impact of New Physics on Momentum-Dependent Particle Widths and Propagators
by: Englert, Christoph, et al.
Published: (2025)

The Pareto Frontier of Resilient Jet Tagging
by: Gambhir, Rikab, et al.
Published: (2025)

QINNs: Quantum-Informed Neural Networks
by: Bal, Aritra, et al.
Published: (2025)

A Lorentz-Equivariant Transformer for All of the LHC
by: Brehmer, Johann, et al.
Published: (2024)

Economical Jet Taggers -- Equivariant, Slim, and Quantized
by: Petitjean, Antoine, et al.
Published: (2025)

Integrating Physics Inspired Features with Graph Convolution
by: Sahu, Rameswar
Published: (2024)

Interpreting Transformers for Jet Tagging
by: Wang, Aaron, et al.
Published: (2024)

Theory-informed neural networks for particle physics
by: Dillon, Barry M., et al.
Published: (2025)

Three-body Entanglement in Particle Decays
by: Sakurai, Kazuki, et al.
Published: (2023)

Looking inside jets: an introduction to jet substructure and boosted-object phenomenology
by: Marzani, Simone, et al.
Published: (2019)

Electroweak corrections and EFT operators in $W^+W^-$ production at the LHC
by: Banerjee, Shankha, et al.
Published: (2024)

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

Another Fit Bites the Dust: Conformal Prediction as a Calibration Standard for Machine Learning in High-Energy Physics
by: Araz, Jack Y., et al.
Published: (2025)

PCN: A Deep Learning Approach to Jet Tagging Utilizing Novel Graph Construction Methods and Chebyshev Graph Convolutions
by: Semlani, Yash, et al.
Published: (2023)

Higgs boson off-shell measurements probe non-linearities
by: Anisha, et al.
Published: (2024)

A Step Toward Interpretability: Smearing the Likelihood
by: Larkoski, Andrew J.
Published: (2025)

Jet Classification Using High-Level Features from Anatomy of Top Jets
by: Furuichi, Amon, et al.
Published: (2023)

Dispelling the $\sqrt{L}$ myth for the High-Luminosity LHC
by: Belvedere, Alberto, et al.
Published: (2024)

A comprehensive study of ALPs from $B$-decays
by: Bisht, Deepanshu, et al.
Published: (2024)

Continuous-variable photonic quantum extreme learning machines for fast collider-data selection
by: Maier, Benedikt, et al.
Published: (2025)

Harnessing Higgs Kinematics for HEFT Constraints
by: Englert, Christoph, et al.
Published: (2025)

Weak boson probes of Higgs unitarity restoration at 10 TeV parton colliders
by: Englert, Christoph, et al.
Published: (2026)

Communicating Likelihoods with Normalising Flows
by: Araz, Jack Y., et al.
Published: (2025)

Electroweak Scalar Effects Beyond Dimension-6 in SMEFT
by: Adhikary, Nilabhra, et al.
Published: (2025)

Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach
by: Gurkanli, Emre, et al.
Published: (2026)