3 papers
cs.CV2026
A Deep Equilibrium Network for Hyperspectral Unmixing
Chentong Wang, Jincheng Gao, Fei Zhu +1
Hyperspectral unmixing (HU) is crucial for analyzing hyperspectral imagery, yet achieving accurate unmixing remains challenging. While traditional methods struggle to effectively m…
cs.CV2025
DTU-Net: A Multi-Scale Dilated Transformer Network for Nonlinear Hyperspectral Unmixing
ChenTong Wang, Jincheng Gao, Fei Zhu +2
Transformers have shown significant success in hyperspectral unmixing (HU). However, challenges remain. While multi-scale and long-range spatial correlations are essential in unmix…
q-bio.BM2024
Towards deep learning sequence-structure co-generation for protein design
Chentong Wang, Sarah Alamdari, Carles Domingo-Enrich +2
Deep generative models that learn from the distribution of natural protein sequences and structures may enable the design of new proteins with valuable functions. While the majorit…