3 papers
cs.CV2026
A Unified Variational Framework for Deep Weakly Supervised Image Segmentation
Yin King Chu, Lingfeng Li, Sung Ha Kang +2
We propose a unified variational framework for image segmentation under sparse pixel-level supervision. Our method is based on a simplex-constrained Potts model with a smooth perim…
cs.LG2026
A Mathematical Explanation of Transformers
Xue-Cheng Tai, Hao Liu, Lingfeng Li +1
The Transformer architecture has revolutionized the field of sequence modeling and underpins the recent breakthroughs in large language models (LLMs). However, a comprehensive math…
cs.LG2026
A level-wise training scheme for learning neural multigrid smoothers with application to integral equations
Lingfeng Li, Yin King Chu, Raymond Chan +1
Convolution-type integral equations commonly occur in signal processing and image processing. Discretizing these equations yields large and ill-conditioned linear systems. While th…