:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Kainan, Huang, Jingyu, Huang, Guihong, Luo, Jianyi
Format:	Preprint
Published:	2026
Subjects:	High Energy Physics - Experiment Machine Learning
Online Access:	https://arxiv.org/abs/2602.05767
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Machine-Learning based photon counting for PMT waveforms and its application to the improvement of the energy resolution in large liquid scintillator detectors
by: Jiang, Wei, et al.
Published: (2024)

Reconstruction of the Effective Energy-deposition Vertex of Muon Showers using PMT Waveform in a Large-scale Liquid Scintillator Detector
by: Zhang, Junwei, et al.
Published: (2025)

Characterization of Deconvolution-Based PMT Waveform Reconstruction Under Large Charge Dynamic Range and Varying Scintillation Time Profiles
by: Lin, Xingyi, et al.
Published: (2026)

Global Fit of KamLAND Data and the Daya Bay Antineutrino Energy Spectrum
by: Huang, Guihong
Published: (2026)

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

DCTracks: An Open Dataset for Machine Learning-Based Drift Chamber Track Reconstruction
by: Liyan, Qian, et al.
Published: (2026)

Investigation and optimization of the deconvolution method for PMT waveform reconstruction
by: Tang, Jingzhe, et al.
Published: (2024)

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

Discriminative versus Generative Approaches to Simulation-based Inference
by: Sluijter, Benjamin, et al.
Published: (2025)

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

Advancing Set-Conditional Set Generation: Diffusion Models for Fast Simulation of Reconstructed Particles
by: Kobylianskii, Dmitrii, et al.
Published: (2024)

Re-Simulation-based Self-Supervised Learning for Pre-Training Foundation Models
by: Harris, Philip, et al.
Published: (2024)

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

Training 3D ResNets to Extract BSM Physics Parameters from Simulated Data
by: Dubey, S., et al.
Published: (2023)

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

Triggering Dark Showers with Conditional Dual Auto-Encoders
by: Anzalone, Luca, et al.
Published: (2023)

Design & Optimization of the HV divider for JUNO 20-inch PMT
by: Luo, Feng-Jiao, et al.
Published: (2023)

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

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

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

3D Magnetic Field Reconstruction and Mapping with Physics-Informed Neural Networks
by: Yu, Haohan, et al.
Published: (2026)

Reconstruction of muon bundles in KM3NeT detectors using machine learning methods
by: Kalaczyński, Piotr
Published: (2025)

Learning Minimal-Deviation Corrections for Multi-Dimensional Mismodelling in HEP Simulations
by: Schott, Matthias, et al.
Published: (2026)

TrackFormers Part 2: Enhanced Transformer-Based Models for High-Energy Physics Track Reconstruction
by: Caron, Sascha, et al.
Published: (2025)

Transfer Learning Across Fast- and Full-Simulation Domains in High-Energy Physics
by: Schott, Matthias, et al.
Published: (2026)

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

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
by: Krause, Claudius, et al.
Published: (2024)

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

Reduced Simulations for High-Energy Physics, a Middle Ground for Data-Driven Physics Research
by: Odyurt, Uraz, et al.
Published: (2023)

Development of a comprehensive PMT optical model for the JUNO experiment
by: Ren, Y., et al.
Published: (2026)

Waveform Simulation in PandaX-4T
by: Li, Jiafu, et al.
Published: (2023)

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

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

Design and Evaluation of a PMT High-Voltage system for Deepsea Neutrino Telescope
by: Mao, Zhu, et al.
Published: (2025)

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

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

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

Conditional Deep Generative Models for Simultaneous Simulation and Reconstruction of Entire Events
by: Dreyer, Etienne, et al.
Published: (2025)

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

PETNet -- Coincident Particle Event Detection using Spiking Neural Networks
by: Debus, Jan, et al.
Published: (2025)