1 citations · 1 across the 4 of their papers we have counts for
6 papers
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…