2 citations · 4 across the 14 of their papers we have counts for
5 papers · 1 filter
Gradient-Update Mismatch: Rethinking Conflict-Free Training of Physics-Informed Neural Networks
Jing Xiao, Xinhai Chen, Qinglin Wang +5
Training Physics-Informed Neural Networks (PINNs) requires jointly optimizing physics residual and initial/boundary condition loss terms, which often induce conflicting gradients.…
Audio-Anchored Fusion of Multi-Ratio DiT Reconstruction Residuals for Cross-Domain Audio Deepfake Detection
Haotian Mo, Jie Liu, Siqi Shen +8
Audio deepfake detectors often degrade when generators, corpora, or recording conditions change. We use a Diffusion Transformer (DiT), trained only on bona fide speech, as a frozen…
HistoGPA: A Context-Conditioned Gene-Prior Attention Framework for Histology-Based Spatial Gene Expression Prediction
Ziang Liu, Xinhai Chen, Yigui Feng +3
Predicting spatial gene expression from routine hematoxylin and eosin (H&E) images provides a practical complement to experimental spatial transcriptomics. Existing approaches focu…
Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning
Yunfei Liu, Hao Wang, Yuhang Qi +8
High-fidelity computational fluid dynamics is essential for aerospace design, but engineering-scale simulations of practical three-dimensional aircraft remain computationally expen…
Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery
Jing Xiao, Xinhai Chen, Jiaming Peng +7
Symbolic Regression (SR) aims to discover interpretable equations from observational data, with the potential to reveal underlying principles behind natural phenomena. However, exi…