孙剑
代表性论文
学术专著：孙剑、徐宗本，《模型驱动的深度学习——模型与数据双驱动的人工智能建模方法》，科学出版社，2025. 章节: (1) 模型与数据双驱动方法概述，(2) 优化模型驱动的深度学习方法，(3)统计模型驱动的深度学习方法， (4) 几何模型驱动的深度学习方法， (5) 微分方程建模与求解的深度学习方法，(6) 结语与展望
代表性论文如下(Link to full list)：
1. 模型驱动深度学习（模型与数据双驱动学习方法）
Jian Sun, Marshall Tappen. Learning Non-local Range Markov Random Field for Image Restoration. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Colorado, USA, 2011. (提出非局部MRF模型, 并通过梯度下降展开过程的反向求导实现MRF统计分布参数学习）
Jian Sun, Marshall Tappen. Separable Markov Random Field and Its Application in Low Level Vision. IEEE Transactions on Image Processing, Vol. 22, No. 1, Pages:402-408, 2013 （学习Markov随机场的可分滤波器组，提高图像处理计算速度）
Jian Sun, Jian Sun, Zongben Xu. Color Image Denoising via Discriminatively Learned Iterative Shrinkage. IEEE Transactions on Image Processing, 24(11):4148-4159, 2015. （将图像正则化项的迭代阈值算法推广为可学习深度结构，采用核回归技术学习非线性变换，从而隐式学习图像正则项）
Yan Yang, Jian Sun*, Huibin Li, Zongben Xu. Deep ADMM-Net for Compressive Sensing MRI, Advances in Neural Information Processing Systems, 2016 （压缩传感正则化先验与模型/算法超参数的自适应学习方法，将压缩传感 / MRI成像物理机制与深度学习结合的最早工作之一）
Yan Yang, Jian Sun*, Huibin Li, Zongben Xu. ADMM-CSNet: A Deep Learning Approach for Image Compressive Sensing. IEEE Trans. on Pattern Recognition and Machine Intelligence, 2019 （将深度学习与一般图像压缩传感成像结合的模型/数据双驱动学习方法）
Zongben Xu*, Jian Sun*. Model-driven Deep Learning, National Science Review, 2018. (模型驱动深度学习的提出论文，为结合领域知识/模型构造深度结构提供思路)
模型与数据双驱动系列工作综述：CSIAM Trans. on Applied Mathematics，https://doc.global-sci.org/uploads/online_news/CSIAM-AM/202009010924-17030.pdf，2020.
2. 人工智能基础模型与算法
Dongyi Wang, Yuanwei Jiang, Zhenyi Zhang, Xiang Gu, Peijie Zhou, Jian Sun, Joint Velocity-Growth Flow Matching for Single-Cell Dynamics Modeling, NeurIPS, 2025
Xi Yu, Xiang Gu, Zhihao Shi, Jian Sun, Wasserstein Style Distribution Analysis and Transform for Stylized Image Generation, ICCV 2025
Xiang Gu, Yucheng Yang, Wei Zeng, Jian Sun, Zongben Xu, Keypoint-Guided Optimal Transport with Applications in Heterogeneous Domain Adaptation, NeurIPS, 2022.
Shipeng Wang, Xiaorong Li, Jian Sun*, Zongben Xu, Training Networks in Null Space of Feature Covariance with Self-Supervision for Incremental Learning (code), IEEE Trans. on Pattern Analysis and Machine Intelligence, 2024.
Xiang Gu, Liwei Yang, Jian Sun*, Zongben Xu, Optimal Transport-Guided Conditional Score-Based Diffusion Model, Neurips, 2023.
Xin Wei, Ruixuan Yu, Jian Sun, View-GCN: View-based Graph Convolutional Network for 3D Shape Analysis, IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2020.
