The Deep Learning Cosmic Ray Energy Reconstruction Pipeline for the GRAPES-3 Experiment

arXiv:2607.07265 · astro-ph.IM, astro-ph.HE, hep-ex · Submitted 2026-07-08 · Read on arXiv

Sambit Sarkar, Mansi Talwar, Pravata K. Mohanty

astro-ph.IM, astro-ph.HE, hep-ex

Submitted: 2026-07-08

Comments: Presented at the 39th International Cosmic Ray Conference (ICRC 2025). 8 pages, 8 figures

Journal ref: PoS(ICRC2025)383 (2025)

DOI: 10.22323/1.501.0383

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Fine-Tuning — 8× in this paper · explained in 5 episodes
Latent Space — 6× in this paper · explained in 7 episodes
Anisotropy — 5× in this paper · explained in 3 episodes
Core — 3× in this paper · explained in 2 episodes
Calibration — 2× in this paper · explained in 7 episodes
Consistency — 2× in this paper · explained in 3 episodes
Adam — 1× in this paper · explained in 2 episodes
Alignment — 1× in this paper · explained in 1 episode
Clustering — 1× in this paper · explained in 2 episodes
Embeddings — 1× in this paper · explained in 2 episodes
Ensemble Learning — 1× in this paper · explained in 2 episodes
GNNs — 1× in this paper · explained in 2 episodes
Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
Latent Representation — 1× in this paper · explained in 2 episodes
Point Clouds — 1× in this paper · explained in 2 episodes

Sources

A Dynamic Reduction Network for Point Clouds

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