Huang, Junzhou

Adaptive Graph Convolutional Neural Networks

Li, R., Wang, S., Zhu, F., & Huang, J. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 842

Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks

Bian, T., Xiao, X., Xu, T., Zhao, P., Huang, W., Rong, Y., & Huang, J. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Misinformation and Its ImpactsComplex Network Analysis Techniques

Cited by 796

Transformer-based unsupervised contrastive learning for histopathological image classification

Wang, X., Yang, S., Zhang, J., Wang, M., Zhang, J., Yang, W., Huang, J., & Han, X. (2022) · Medical Image Analysis

AI in cancer detectionDomain Adaptation and Few-Shot Learning

Cited by 751

scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data

Yang, F., Wang, W., Wang, F., Fang, Y., Tang, D., Huang, J., Lu, H., & Yao, J. (2021) · Nature Machine Intelligence

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 617

Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks

Yao, J., Zhu, X., Jonnagaddala, J., Hawkins, N., & Huang, J. (2020) · Medical Image Analysis

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 522

Progressive Feature Alignment for Unsupervised Domain Adaptation

Chen, C., Xie, W., Huang, W., Rong, Y., Ding, X., Huang, Y., Xu, T., & Huang, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 481

Vision-Language Pre-Training with Triple Contrastive Learning

Yang, J., Duan, J., Tran, S., Xu, Y., Chanda, S., Chen, L., Zeng, B., Chilimbi, T., & Huang, J. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 309

Towards robust and effective shape modeling: Sparse shape composition

Zhang, S., Zhan, Y., Dewan, M., Huang, J., Metaxas, D. N., & Zhou, X. S. (2012) · Medical Image Analysis

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 249

RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval

Wang, X., Du, Y., Yang, S., Zhang, J., Wang, M., Zhang, J., Yang, W., Huang, J., & Han, X. (2023) · Medical Image Analysis

AI in cancer detectionImage Retrieval and Classification Techniques

Cited by 218

TransPath: Transformer-Based Self-supervised Learning for Histopathological Image Classification

Wang, X., Yang, S., Zhang, J., Wang, M., Zhang, J., Huang, J., Yang, W., & Han, X. (2021) · Lecture Notes in Computer Science

AI in cancer detectionDomain Adaptation and Few-Shot Learning

Cited by 178

Application advances of deep learning methods for de novo drug design and molecular dynamics simulation

Bai, Q., Liu, S., Tian, Y., Xu, T., Banegas‐Luna, A. J., Pérez‐Sánchez, H., Huang, J., Liu, H., & Yao, X. (2022) · WIREs Computational Molecular Science

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 156

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

Xia, P., Chen, Z., Tian, J., Gong, Y., Hou, R., Xu, Y., Wu, Z., Fan, Z., Zhou, Y., Zhu, K., et al. (2024) · Advances in Neural Information Processing Systems 37

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 32

Joint Kernel-Based Supervised Hashing for Scalable Histopathological Image Analysis

Jiang, M., Zhang, S., Huang, J., Yang, L., & Metaxas, D. N. (2015) · Lecture Notes in Computer Science

Image Retrieval and Classification TechniquesAI in cancer detection

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