activity
20212026
most citedTemperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks

96 citations · 245 across the 21 of their papers we have counts for

collaborators

22 papers

cs.LG2026

MTL-FNO: A Lightweight Multi-Task Fourier Neural Operator for Sparse Field Reconstruction

Siyu Ye, Shihang Li, Zhiqiang Gong +4

Efficient onboard multi-field sparse reconstruction is essential for the autonomous operation of aerospace vehicles. While existing deep learning models exhibit promise for single-…

cs.CV2025

SynergyWarpNet: Attention-Guided Cooperative Warping for Neural Portrait Animation

Shihang Li, Zhiqiang Gong, Minming Ye +2

Recent advances in neural portrait animation have demonstrated remarked potential for applications in virtual avatars, telepresence, and digital content creation. However, traditio…

cs.LG2025

Learning to Reconstruct Temperature Field from Sparse Observations with Implicit Physics Priors

Shihang Li, Zhiqiang Gong, Weien Zhou +2

Accurate reconstruction of temperature field of heat-source systems (TFR-HSS) is crucial for thermal monitoring and reliability assessment in engineering applications such as elect…

physics.flu-dyn2025

A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement

Yanfang Lyu, Yunyang Zhang, Zhiqiang Gong +3

Deep learning has shown promise in improving computing efficiency while ensuring modeling accuracy in fluid-structure interaction (FSI) analysis. However, its current capabilities…

cs.CV2023

MultiScale Spectral-Spatial Convolutional Transformer for Hyperspectral Image Classification

Zhiqiang Gong, Xian Zhou, Wen Yao

Due to the powerful ability in capturing the global information, Transformer has become an alternative architecture of CNNs for hyperspectral image classification. However, general…

cs.CV2023

Deep Intrinsic Decomposition with Adversarial Learning for Hyperspectral Image Classification

Zhiqiang Gong, Xian Zhou, Wen Yao

Convolutional neural networks (CNNs) have been demonstrated their powerful ability to extract discriminative features for hyperspectral image classification. However, general deep…