5 papers
RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models
Qian Sun, Yong-Ming Tian, Jia-Wei Huang +2
Recent years have witnessed the emergence of multivariate modeling using time series foundation models (TSFMs), which achieve advanced zero-shot generalization. Modern multivariate…
HyperPriv-EPN: Hypergraph Learning with Privileged Knowledge for Ependymoma Prognosis
Shuren Gabriel Yu, Sikang Ren, Yongji Tian
Preoperative prognosis of Ependymoma is critical for treatment planning but challenging due to the lack of semantic insights in MRI compared to post-operative surgical reports. Exi…
A Unified Kernel for Neural Network Learning
Shao-Qun Zhang, Zong-Yi Chen, Yong-Ming Tian +1
Past decades have witnessed a great interest in the distinction and connection between neural network learning and kernel learning. Recent advancements have made theoretical progre…
Depth-induced NTK: Bridging Over-parameterized Neural Networks and Deep Neural Kernels
Yong-Ming Tian, Shuang Liang, Shao-Qun Zhang +1
While deep learning has achieved remarkable success across a wide range of applications, its theoretical understanding of representation learning remains limited. Deep neural kerne…
A CT Image Classification Network Framework for Lung Tumors Based on Pre-trained MobileNetV2 Model and Transfer learning, And Its Application and Market Analysis in the Medical field
Ziyang Gao, Yong Tian, Shih-Chi Lin +1
In the medical field, accurate diagnosis of lung cancer is crucial for treatment. Traditional manual analysis methods have significant limitations in terms of accuracy and efficien…