References

[1]
Søren Hauberg. Latent machine learning geometry. Lecture notes, 2026. Accessed: 2026-08-20.
[2]
Ilyes Khemakhem, Diederik Kingma, Ricardo Monti, and Aapo Hyvarinen. Variational autoencoders and nonlinear ica: A unifying framework. In Silvia Chiappa and Roberto Calandra, editors, Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, volume 108 of Proceedings of Machine Learning Research, pages 2207–2217. PMLR, 26–28 Aug 2020.
[3]
Aapo Hyvarinen, Hiroaki Sasaki, and Richard Turner. Nonlinear ica using auxiliary variables and generalized contrastive learning. In Kamalika Chaudhuri and Masashi Sugiyama, editors, Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, volume 89 of Proceedings of Machine Learning Research, pages 859–868. PMLR, 16–18 Apr 2019.
[4]
M. E. Tipping and Christopher Bishop. Probabilistic principal component analysis. Journal of the Royal Statistical Society, Series B, 21(3):611–622, January 1999. Available from http://www.ncrg.aston.ac.uk/Papers/index.html.
[5]
Quentin F. Gronau, Alexandra Sarafoglou, Dora Matzke, Alexander Ly, Udo Boehm, Maarten Marsman, David S. Leslie, Jonathan J. Forster, Eric-Jan Wagenmakers, and Helen Steingroever. A tutorial on bridge sampling, 2017.
[6]
Max Hinne. An introduction to sequential monte carlo for bayesian inference and model comparison—with examples for psychology and behavioral science. Behavior Research Methods, 57:125, 03 2025.
[7]
Bowen Jin, Hansi Zeng, Zhenrui Yue, Jinsung Yoon, Sercan Arik, Dong Wang, Hamed Zamani, and Jiawei Han. Search-r1: Training llms to reason and leverage search engines with reinforcement learning, 2025.
[8]
Lang Mei, Zhihan Yang, Xiaohan Yu, Huanyao Zhang, and Chong Chen. Ai-searchplanner: Modular agentic search via pareto-optimal multi-objective reinforcement learning, 2025.
[9]
Johan Bjorck, Carla P. Gomes, and Bart Selman. Understanding batch normalization. CoRR, abs/1806.02375, 2018.
[10]
Sergey Ioffe and Christian Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift, 2015.
[11]
Junjie Yan, Ruosi Wan, Xiangyu Zhang, Wei Zhang, Yichen Wei, and Jian Sun. Towards stabilizing batch statistics in backward propagation of batch normalization, 2020.
[12]
Caio S. Rohwedder, João P. L. de Carvalho, José Nelson Amaral, Guido Araújo, Giancarlo Colmenares, and Kai-Ting Amy Wang. Pooling acceleration in the davinci architecture using im2col and col2im instructions. In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pages 46–55, 2021.
[13]
Wilson W.L. Fung, Ivan Sham, George Yuan, and Tor M. Aamodt. Dynamic warp formation and scheduling for efficient gpu control flow. In 40th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2007), pages 407–420, 2007.