15 citations · 28 across the 6 of their papers we have counts for
6 papers
scGTN: Deep Siamese Graph Transformer Network for Single-cell RNA Sequencing Clustering
Jinke Wu, Yifan Wang, Siyu Yi +5
Single-cell RNA sequencing (scRNA-seq) serves a pivotal role in characterizing gene expression at the cellular level, enabling the identification of cell types and advancing the un…
Dual Prompt Learning for Adapting Vision-Language Models to Downstream Image-Text Retrieval
Yifan Wang, Tao Wang, Chenwei Tang +5
Recently, prompt learning has demonstrated remarkable success in adapting pre-trained Vision-Language Models (VLMs) to various downstream tasks such as image classification. Howeve…
Evolution Meets Diffusion: Efficient Neural Architecture Generation
Bingye Zhou, Caiyang Yu, Chenwei Tang
Neural Architecture Search (NAS) has gained widespread attention for its transformative potential in deep learning model design. However, the vast and complex search space of NAS l…
Analysis and Applications of Deep Learning with Finite Samples in Full Life-Cycle Intelligence of Nuclear Power Generation
Chenwei Tang, Wenqiang Zhou, Dong Wang +8
The advent of Industry 4.0 has precipitated the incorporation of Artificial Intelligence (AI) methods within industrial contexts, aiming to realize intelligent manufacturing, opera…
GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model
Caiyang Yu, Xianggen Liu, Yifan Wang +5
Neural Architecture Search (NAS) has emerged as one of the effective methods to design the optimal neural network architecture automatically. Although neural architectures have ach…
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…