相关的资料

视频:

• https://www.bilibili.com/video/BV1aE411o7qd

• https://www.bilibili.com/video/BV17ZmWBmETP/

github: https://github.com/tsyw/MachineLearningNotes

语雀: https://www.yuque.com/books/share/f4031f65-70c1-4909-ba01-c47c31398466?#

机器学习白板推导

基础部分 (要求)

1. 绪论

2. 数学基础

3. 线性回归

4. 线性分类

5. 降维

   • Face recognition using eigenfaces

6. 支持向量机

7. 核方法

8. 指数族分布

   • Probablistic population codes

9. 概率图模型

10. EM算法

    • Batchelder, W. H., & Riefer, D. M. (1999). Theoretical and empirical review of multinomial process tree modeling

11. 高斯混合模型

    • (心理学应用待补充)

12. 变分推断

    • 变分推断求解心理物理曲线

    • Gershman, S. J. (2019). What does the free energy principle tell us about the brain?. Neurons, Behavior, Data analysis, and Theory, 2(3), 1-10. https://gershmanlab.com/pubs/free_energy.pdf

13. MCMC

    • MCMC求解心理物理曲线

    • Neural Sampling Hypothesis

14. HMM

    • Visser, I., Raijmakers, M. E. J., & Molenaar, P. C. M. (1999). Hidden Markov models for individual time series: An application to the sequential learning data. https://link.springer.com/content/pdf/10.1007/978-0-387-95922-1_13

15. linear dynamic system

    • Kwon, O. S., Tadin, D., & Knill, D. C. (2015). Unifying account of visual motion and position perception. Proceedings of the National Academy of Sciences, 112(26), 8142-8147.

    • Malamud, J., Guloksuz, S., van Winkel, R., Delespaul, P., De Hert, M. A. F., Derom, C., Thiery, E., Jacobs, N., Rutten, B. P. F., & Huys, Q. J. M. (2024). “Characterizing the dynamics, reactivity and controllability of moods in depression with a Kalman filter.” PLOS Computational Biology , 20(9): e1012457

16. Particle filter

    • Sanborn, A. N., Griffiths, T. L., & Navarro, D. J. (2010). Rational approximations to rational models: Alternative algorithms for category learning . Psychological Review, 117(4), 1144-1167.

    • Modeling the effect of chained study in transitive inference. 代码: https://github.com/fangzefunny/particle-filter; 论文: https://escholarship.org/uc/item/4764d1tn

17. 生成模型

    • Organizing probablistic models of perception

    • The Bayesian brain: the role of uncertainty in neural coding and computation

18. GAN

    • Goetschalckx, L., Andonian, A., & Wagemans, J. (2021). Generative adversarial networks unlock new methods for cognitive science. Trends in Cognitive Sciences, 25(9), 788-801.

19. VAE

    • A model of working memory for latent representations

    • A generative model of memory construction and consolidation

20. Hopefield Network

    •  

21.  

进阶部分(不要求)

1. 前馈神经网络

2. 高斯网络

3. 贝叶斯线性回归

4. 高斯过程回归

5. Normalizing flow

6. 条件随机场

7. Restricted Bolzman Machine

8. 谱聚类

9. 直面配分函数

10. 近似推断

11. Sigmoid Belief Network

12. Deep Belief Network

13. Bolzman Machine

14. Deep Bolzman Machine