cml

https://github.com/rguo12/awesome-causality-algorithms

https://github.com/salesforce/causalai

https://ftp.cs.ucla.edu/pub/stat_ser/r514.pdf

https://blog.ml.cmu.edu/2022/11/28/causal-confounds-in-sequential-decision-making/?utm_campaign=Artificial%2BIntelligence%2BWeekly&utm_medium=email&utm_source=Artificial_Intelligence_Weekly_305

https://openreview.net/pdf?id=TsXe-CyYJqx

https://colab.research.google.com/drive/13Bsvvl5l3uR1hbVdpMAFR13gdjwoJ6if?usp=sharing

https://d2cml-ai.github.io/d2cml.ai/

https://drive.google.com/file/d/1wNyDm2j03YzVW7g8w5NkFdrMakw5lId5/view

https://github.com/py-why/dowhy/blob/main/docs/source/example_notebooks/tutorial-causalinference-machinelearning-using-dowhy-econml.ipynb

https://ftp.cs.ucla.edu/pub/stat_ser/r493-reprint.pdf

https://www.amazon.science/blog/causal-inference-when-treatments-are-continuous-variables

https://arxiv.org/pdf/2206.15475.pdf

https://www.microsoft.com/en-us/research/group/causal-inference/projects/

https://github.com/lucidrains/DALLE2-pytorch

https://fentechsolutions.github.io/CausalDiscoveryToolbox/html/index.html

What if book https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ https://github.com/jrfiedler/causal_inference_python_code

https://theeffectbook.net/

https://www.bradyneal.com/causal-inference-course

causalnex https://github.com/quantumblacklabs/causalnex

causality handbook https://github.com/matheusfacure/python-causality-handbook

https://lbynum.github.io/interactive-causal-inference/

causal discovery from videos https://github.com/pairlab/v-cdn

Automated Learning and Intelligence for Causation and Economics https://github.com/microsoft/EconML

https://p-hunermund.com/2019/05/06/causal-data-science-in-business/

https://towardsdatascience.com/introduction-to-causality-in-machine-learning-4cee9467f06f

https://www.altdeep.ai/p/causal-ml-minicourse https://github.com/robertness/causalML/blob/master/tutorials/3-counterfactual/counterfactual_donuts_tutorial.ipynb

https://nips.cc/virtual/2020/public/invited_16169.html

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjQ-9D-oaT1AhW_R_EDHXfWAO0QFnoECAQQAQ&url=https%3A%2F%2Farxiv.org%2Fabs%2F2009.13472&usg=AOvVaw1u7rcNSEzm3HYYMhFeGSXe

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwiSuOucoaT1AhXvQvEDHc5ZC64QFnoECAUQAQ&url=https%3A%2F%2Facademic.oup.com%2Fectj%2Farticle%2F21%2F1%2FC1%2F5056401&usg=AOvVaw1N8XUu73y9T7t7ufju__zD

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwio1YmWoqT1AhVBSvEDHaRCDFIQFnoECAQQAQ&url=https%3A%2F%2Farxiv.org%2Fabs%2F2004.08697&usg=AOvVaw2AfQIf7K8gpSKxREuNPafv

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwiQxNHAoqT1AhXGR_EDHWTbCrUQFnoECAQQAQ&url=https%3A%2F%2Farxiv.org%2Fabs%2F2112.02761&usg=AOvVaw2gfEGCjez4OtOWrApgwNEa

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwj69pneoaT1AhWiSvEDHRxBB6wQFnoECAoQAw&url=https%3A%2F%2Farxiv.org%2Fabs%2F2109.11990&usg=AOvVaw3yz9vFUIrAIvKDyCok-mJm

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwiK97jXnqT1AhX8SvEDHTZ5C8IQFnoECAQQAQ&url=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs42256-020-0218-x&usg=AOvVaw1tIZXDXhg2r9fWnKakQScc

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjKhay3n6T1AhWNS_EDHZlYA88QFnoECAYQAQ&url=https%3A%2F%2Farxiv.org%2Fabs%2F2102.12353&usg=AOvVaw040PYsOOYFT_0l40W9KAF3

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwipnZy2oaT1AhXRSvEDHYp5AxAQFnoECAYQAQ&url=https%3A%2F%2Farxiv.org%2Fabs%2F1906.02226&usg=AOvVaw3hnA6PyPAuOrmNAjcUoF3g

https://causalinference.gitlab.io/books/

https://github.com/Microsoft/dowhy

https://github.com/grf-labs/grf

https://github.com/uber/causalml

https://github.com/pgmpy/pgmpy

https://github.com/jtextor/dagitty

https://arxiv.org/pdf/2007.10152.pdf

https://github.com/biomedia-mira/deepscm

https://github.com/xunzheng/notears

https://medium.com/data-science-at-microsoft/causal-inference-part-1-of-3-understanding-the-fundamentals-816f4723e54a

https://arxiv.org/pdf/2012.09092.pdf

https://github.com/interpretml/DiCE

https://github.com/google/CausalImpact

https://doi.org/10.1038/s43588-020-00005-8

https://assets.amazon.science/2a/60/aff3520f4d52bb195f4a674ae413/debiasing-concept-based-explanations-with-causal-analysis.pdf

https://github.com/jakobrunge/tigramite

https://plato.stanford.edu/entries/causal-models/index.html#toc

https://www.inference.vc/untitled/

https://fabiandablander.com/r/Causal-Inference.html

https://fairmlbook.org/

https://mlstory.org/causal-practice.html

https://causalscience.org/blog/what-is-causal-data-fusion

https://blog.ml.cmu.edu/2020/08/31/7-causality/

https://bookdown.org/connect/#/apps/2584/access

https://resources.flowcast.ai/resources/causal-intelligence-in-machine-learning/

https://arxiv.org/pdf/1705.08821.pdf

https://github.com/AWehenkel/Graphical-Normalizing-Flows

https://arxiv.org/pdf/1906.02226.pdf

https://arxiv.org/abs/1809.09337

https://mixtape.scunning.com/

https://github.com/IBM/causallib

https://github.com/lujonathanh/BETS

https://github.com/ronikobrosly/causal-curve

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjdzryFn6T1AhWwRvEDHeHcAEUQFnoECAcQAQ&url=http%3A%2F%2Fproceedings.mlr.press%2Fv139%2Fmastakouri21a.html&usg=AOvVaw2oAkQDcSL4CGM_11Zw829S

https://github.com/huawei-noah/trustworthyAI/tree/master/gcastle

https://www.pymc-labs.io/blog-posts/causalpy-a-new-package-for-bayesian-causal-inference-for-quasi-experiments/

https://journals.sagepub.com/doi/10.1177/25152459221095823

https://www.emilyriederer.com/post/causal-data/

https://arxiv.org/pdf/2305.16183.pdf