2 citations · 3 across the 9 of their papers we have counts for
10 papers
Coupled Optimal Transport with Landmark Constraints
Xiang Gu, Jian Sun, Zongben Xu
Existing optimal transport (OT) models primarily seek an OT map or plan between distributions by minimizing a prescribed transport cost or distortion. However, minimizing transport…
NEPMaker: Active learning of neuroevolution machine learning potential for large cells
Junjie Wang, Shuning Pan, Haoting Zhang +4
Machine learning potentials (MLPs) achieve near first-principles accuracy but often fail for atomic environments outside the training distribution. Active learning can mitigate thi…
A Residual-Shell-Based Lower Bound for Ollivier-Ricci Curvature
Xiang Gu, Huichun Zhang, Jian Sun
Ollivier-Ricci curvature (ORC), defined via the Wasserstein distance that captures rich geometric information, has received growing attention in both theory and applications. Howev…
Generating transition states of chemical reactions via distance-geometry-based flow matching
Yufei Luo, Xiang Gu, Jian Sun
Transition states (TSs) are crucial for understanding reaction mechanisms, yet their exploration is limited by the complexity of experimental and computational approaches. Here we…
BaryIR: Learning Multi-Source Unified Representation in Continuous Barycenter Space for Generalizable All-in-One Image Restoration
Xiaole Tang, Xiaoyi He, Xiang Gu +1
Despite remarkable advances made in all-in-one image restoration (AIR) for handling different types of degradations simultaneously, existing methods remain vulnerable to out-of-dis…
Towards Prospective Medical Image Reconstruction via Knowledge-Informed Dynamic Optimal Transport
Taoran Zheng, Yan Yang, Xing Li +3
Medical image reconstruction from measurement data is a vital but challenging inverse problem. Deep learning approaches have achieved promising results, but often requires paired m…
Joint Velocity-Growth Flow Matching for Single-Cell Dynamics Modeling
Dongyi Wang, Yuanwei Jiang, Zhenyi Zhang +3
Learning the underlying dynamics of single cells from snapshot data has gained increasing attention in scientific and machine learning research. The destructive measurement techniq…
GMapLatent: Geometric Mapping in Latent Space
Wei Zeng, Xuebin Chang, Jianghao Su +3
Cross-domain generative models based on encoder-decoder AI architectures have attracted much attention in generating realistic images, where domain alignment is crucial for generat…
Degradation-Aware Residual-Conditioned Optimal Transport for Unified Image Restoration
Xiaole Tang, Xiang Gu, Xiaoyi He +2
All-in-one image restoration has emerged as a practical and promising low-level vision task for real-world applications. In this context, the key issue lies in how to deal with dif…
Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
Xiaole Tang, Xin Hu, Xiang Gu +1
Deep learning-based image restoration methods generally struggle with faithfully preserving the structures of the original image. In this work, we propose a novel Residual-Conditio…