Cover Image

PETNet -- Coincident Particle Event Detection using Spiking Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Debus, Jan, Debus, Charlotte, Dissertori, Günther, Götz, Markus
Format:	Preprint
Published:	2025
Subjects:	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

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

Guided Quantum Compression for High Dimensional Data Classification
by: Belis, Vasilis, et al.
Published: (2024)

Learning Reduced Representations for Quantum Classifiers
by: Odagiu, Patrick, et al.
Published: (2025)

Quantum anomaly detection in the latent space of proton collision events at the LHC
by: Belis, Vasilis, et al.
Published: (2023)

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

Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks
by: Khot, Ayush, et al.
Published: (2025)

Scalable Multi-Task Learning for Particle Collision Event Reconstruction with Heterogeneous Graph Neural Networks
by: Sutcliffe, William, et al.
Published: (2025)

Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion
by: Shmakov, Alexander, et al.
Published: (2024)

Reconstruction of Unstable Heavy Particles Using Deep Symmetry-Preserving Attention Networks
by: Fenton, Michael James, et al.
Published: (2023)

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

Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC
by: Puljak, Ema, et al.
Published: (2025)

A Language Model for Particle Tracking
by: Huang, Andris, et al.
Published: (2024)

Bumblebee: Foundation Model for Particle Physics Discovery
by: Wildridge, Andrew J., et al.
Published: (2024)

Modelling Coincident Particle Production in Ultraperipheral Heavy Ion Collisions
by: Harland-Lang, L. A.
Published: (2025)

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

EveNet: A Foundation Model for Particle Collision Data Analysis
by: Hsu, Ting-Hsiang, et al.
Published: (2026)

Graph Neural Network for Neutrino Physics Event Reconstruction
by: Hewes, V, et al.
Published: (2024)

2D Convolutional Neural Network for Event Reconstruction in IceCube DeepCore
by: Peterson, J. H., et al.
Published: (2023)

Uncovering Hidden Systematics in Neural Network Models for High Energy Physics
by: Flek, Lucie, et al.
Published: (2026)

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

PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
by: Leigh, Matthew, et al.
Published: (2023)

Softly Induced Functional Simplicity: Implications for Neural Network Generalisation, Robustness, and Distillation
by: Glowacki, Maciej
Published: (2026)

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

Heterogeneous Point Set Transformers for Segmentation of Multiple View Particle Detectors
by: Robles, Edgar E., et al.
Published: (2025)

Particle identification with machine learning from incomplete data in the ALICE experiment
by: Karwowska, Maja, et al.
Published: (2024)

Novel Approaches for ML-Assisted Particle Track Reconstruction and Hit Clustering
by: Odyurt, Uraz, et al.
Published: (2024)

Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction
by: Govil, Shitij, et al.
Published: (2025)

DINAMO: Dynamic and INterpretable Anomaly MOnitoring for Large-Scale Particle Physics Experiments
by: Gavrikov, Arsenii, et al.
Published: (2025)

Human-in-the-loop Reinforcement Learning for Data Quality Monitoring in Particle Physics Experiments
by: Parra, Olivia Jullian, et al.
Published: (2024)

Feed-Forward Optimization With Delayed Feedback for Neural Network Training
by: Flügel, Katharina, et al.
Published: (2023)

Denoising Graph Super-Resolution towards Improved Collider Event Reconstruction
by: Kakati, Nilotpal, et al.
Published: (2024)

TrackFormers: In Search of Transformer-Based Particle Tracking for the High-Luminosity LHC Era
by: Caron, Sascha, 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)

Enhancing High-Energy Particle Physics Collision Analysis through Graph Data Attribution Techniques
by: Verdone, A., et al.
Published: (2024)

Particle Hit Clustering and Identification Using Point Set Transformers in Liquid Argon Time Projection Chambers
by: Robles, Edgar E., et al.
Published: (2025)

Simulation-Prior Independent Neural Unfolding Procedure
by: Butter, Anja, et al.
Published: (2025)

Uncertainty Quantification From Scaling Laws in Deep Neural Networks
by: Elsharkawy, Ibrahim, et al.
Published: (2025)

Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning
by: Gandrakota, Abhijith, et al.
Published: (2024)

Hierarchical Neural Simulation-Based Inference Over Event Ensembles
by: Heinrich, Lukas, et al.
Published: (2023)

An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training
by: Backes, Mathias, et al.
Published: (2022)