- 用Python实现深度学习框架
- Geometry of Deep Learning
- 核函数和卷积
- 神经网络的几何
- Elements of Dimensionality Reduction and Manifold Learning
- 数据集的特征
- 从热动力学到深度学习
- Feynman and Computation Exploring the Limits of Computers
- Hopfield网络
- Information Theory From Coding to Learning
- 变分和优化
- 度量几何视角下的信息理论
- Information Geometry and Its Applications
- Reinforcement Learning and Optimal Control
- The Principles of Deep Learning Theory