├── .gitignore ├── LICENSE ├── README.md ├── images ├── L_v1_v2.png ├── cmc_gif.gif ├── cookie_given_a.jpg ├── cookie_given_aa.jpg ├── edge_to_node.png ├── gnn_graph.png ├── hierarchical_models1.jpg ├── hierarchical_models2.jpg ├── hierarchical_models3.jpg ├── hierarchical_models4.jpg ├── hierarchical_models5.jpg ├── learning_from_many_views.png ├── node_to_edge.png ├── redshift_fig5.png ├── redshift_table1.png ├── size_principle.svg ├── understanding_betavae.png └── value_vs_perceived_value.jpg ├── notebooks ├── Noise_Contrastive_Estimation_Experiments.ipynb └── Transformer - Illustration and code.ipynb ├── notes ├── SimCLR.md ├── amdim.md ├── betavae.md ├── classify_without_labels.md ├── cmc_notes.md ├── contrastive_predictive_coding.md ├── cvpr2024 │ └── neural_redshift.md ├── deepinfomax.md ├── iic.md ├── mine.md ├── moco.md ├── moco_v2.md ├── on_mi_maximization.md ├── probmods │ ├── Chapter 10_ Learning with a language of thought.md │ ├── Chapter 11_ Hierarchical models.md │ ├── Chapter 12_ Occam's Razor.md │ ├── Chapter 13_ Learning (deep) continuous functions.md │ ├── Chapter 14_ Mixture models.md │ ├── Chapter 15_ Social Cognition.md │ ├── Chapter 3_ Conditioning.md │ ├── Chapter 4_ Causal and Statistical Dependence.md │ ├── Chapter 5_ Conditional dependence.md │ ├── Chapter 6_ Bayesian data analysis.md │ ├── Chapter 7_ Algorithms for inference.md │ └── Chapter 9_ Learning as conditional inference.md ├── understanding_betavae.md └── unsupervised_disentanglement.md └── pdfs ├── 1502.05767.pdf └── autodiff.pdf /.gitignore: -------------------------------------------------------------------------------- 1 | notebooks/.ipynb_checkpoints/* 2 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/vinsis/math-and-ml-notes/HEAD/LICENSE -------------------------------------------------------------------------------- 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