1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2025★ 1 cited
Learning and Interpreting Gravitational-Wave Features from CNNs with a Random Forest Approach
Jun Tian, He Wang, Jibo He +3
Convolutional neural networks (CNNs) have become widely adopted in gravitational wave (GW) detection pipelines due to their ability to automatically learn hierarchical features fro…
astro-ph.HE2024★ 1 cited
Cosmological Model Independent Constraints on Lorentz Invariance Violation with Updated Gamma-Ray Burst Observations: An Artificial Neural Network Approach
Jun Tian, Yu Pan, Shuo Cao +2
Searching for Lorentz invariance violation (LIV) using astrophysical sources such as gamma-ray bursts (GRBs) is crucial for probing quantum gravity. However, the dependence of LIV…
astro-ph.CO2023
Testing the spatial geometry of the universe with TianQin: the prospect of using supermassive black hole binaries
Yu Pan, Jingwang Diao, Jing-Zhao Qi +3
The determination of the spatial geometry of the universe plays an important role in modern cosmology. Any deviation from the cosmic curvature would have a profound impact…