Author

Sha, Yu

INSPIRE profile3094677 ORCID0000-0003-4521-2077

2 papers·0 citations in this corpus

	Paper	Category
Mar 26, 2026#32603.24088	Deep learning approaches to extract nuclear deformation parameters from initial-state information in heavy-ion collisions Jun-Qi Tao🇨🇳 · Yang Liu🇨🇳 · Yu Sha🇨🇳 · Xiang Fan🇨🇳 · Yan-Sheng Tu🇨🇳 · Kai Zhou🇨🇳 · Hua Zheng🇨🇳 · Ben-Wei Zhang🇨🇳	nucl-th	—	0
Nov 18, 2025#52511.13163	A deep learning approach for predicting multiple observables in Au+Au collisions at RHIC Jun-Qi Tao🇨🇳 · Xiang Fan🇨🇳 · Yang Liu🇨🇳 · Yu Sha🇨🇳 · Kai Zhou🇨🇳 · Hua Zheng🇨🇳 · Ben-Wei Zhang🇨🇳	nucl-th	PRC	0

Deep learning approaches to extract nuclear deformation parameters from initial-state information in heavy-ion collisions
Jun-Qi Tao🇨🇳 · Yang Liu🇨🇳 · Yu Sha🇨🇳 · Xiang Fan🇨🇳 · Yan-Sheng Tu🇨🇳 · Kai Zhou🇨🇳 · Hua Zheng🇨🇳 · Ben-Wei Zhang🇨🇳
Mar 26, 2026#3nucl-th0 citations
A deep learning approach for predicting multiple observables in Au+Au collisions at RHIC
Jun-Qi Tao🇨🇳 · Xiang Fan🇨🇳 · Yang Liu🇨🇳 · Yu Sha🇨🇳 · Kai Zhou🇨🇳 · Hua Zheng🇨🇳 · Ben-Wei Zhang🇨🇳
Nov 18, 2025#5nucl-thPRC0 citations

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Sha, Yu

Deep learning approaches to extract nuclear deformation parameters from initial-state information in heavy-ion collisions

A deep learning approach for predicting multiple observables in Au+Au collisions at RHIC