activity
20222026
most citedPartial Differential Equations Meet Deep Neural Networks: A Survey

15 citations · 15 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Intra-Modal Neighbors Never Lie: Rectifying Inter-Modal Noisy Correspondence via Graph-Based Intra-Modal Reasoning

Yang Liu, Wentao Feng, Shu-Dong Huang +2

Large-scale web-harvested datasets have fueled the progress of cross-modal retrieval but inevitably suffer from noisy correspondence, which severely degrades model generalization.…

cs.LG2025

HyperNAS: Enhancing Architecture Representation for NAS Predictor via Hypernetwork

Jindi Lv, Yuhao Zhou, Yuxin Tian +3

Time-intensive performance evaluations significantly impede progress in Neural Architecture Search (NAS). To address this, neural predictors leverage surrogate models trained on pr…

cs.CV2025

PCSR: Pseudo-label Consistency-Guided Sample Refinement for Noisy Correspondence Learning

Zhuoyao Liu, Yang Liu, Wentao Feng +1

Cross-modal retrieval aims to align different modalities via semantic similarity. However, existing methods often assume that image-text pairs are perfectly aligned, overlooking No…

cs.CV2025

Aligning Information Capacity Between Vision and Language via Dense-to-Sparse Feature Distillation for Image-Text Matching

Yang Liu, Wentao Feng, Zhuoyao Liu +2

Enabling Visual Semantic Models to effectively handle multi-view description matching has been a longstanding challenge. Existing methods typically learn a set of embeddings to fin…

cs.LG202215 cited

Partial Differential Equations Meet Deep Neural Networks: A Survey

Shudong Huang, Wentao Feng, Chenwei Tang +1

Many problems in science and engineering can be represented by a set of partial differential equations (PDEs) through mathematical modeling. Mechanism-based computation following P…