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

书籍介绍：https://mp.weixin.qq.com/s/oC2Ux9ANRY9fnmweKD9vlQ

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.