# Bayesian Modeling and Causal Inference

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/bayesian-modeling-and-causal-inference-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 1,062,809 |
| Description | This cluster of papers focuses on the learning, inference, and applications of Bayesian networks and related probabilistic graphical models. It covers topics such as causal inference, graphical model structure learning, Markov logic networks, and the use of imprecise probabilities in modeling. The papers also discuss various algorithms for probabilistic learning and highlight the applications of Bayesian networks in diverse fields such as ecology, healthcare, and decision making under uncertainty. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | https://openalex.org/T11303 |
| Works | 57,156 |

## Topic researchers

Showing 12 of 20.

- [Eric S. Lander](https://scholariq.org/researchers/eric-s-lander/)
- [Yoshua Bengio](https://scholariq.org/researchers/yoshua-bengio/)
- [Geoffrey E. Hinton](https://scholariq.org/researchers/geoffrey-e-hinton/)
- [Daniel Kahneman](https://scholariq.org/researchers/daniel-kahneman/)
- [Steven L. Salzberg](https://scholariq.org/researchers/steven-l-salzberg/)
- [Amos Tversky](https://scholariq.org/researchers/amos-tversky/)
- [Karl Friston](https://scholariq.org/researchers/karl-friston/)
- [Donald B. Rubin](https://scholariq.org/researchers/donald-b-rubin/)
- [Trevor Hastie](https://scholariq.org/researchers/trevor-hastie/)
- [John C. Morris](https://scholariq.org/researchers/john-c-morris/)
- [Leo Breiman](https://scholariq.org/researchers/leo-breiman/)
- [Jerome H. Friedman](https://scholariq.org/researchers/jerome-h-friedman/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.