# Bayesian Modeling and Causal Inference
**Type:** Topics
**Canonical URL:** https://scholariq.org/topics/bayesian-modeling-and-causal-inference/
## Facts
| Field | Value |
| --- | --- |
| 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 | t11303 |
| Works | 65 |
## Topic papers all
Showing 15 of 65.
- [From local explanations to global understanding with explainable AI for trees](https://scholariq.org/papers/from-local-explanations-to-global-understanding-with-explainable-ai-for-trees/)
- [A Bayesian Method for the Induction of Probabilistic Networks from Data](https://scholariq.org/papers/a-bayesian-method-for-the-induction-of-probabilistic-networks-from-data/)
- [A Bayesian method for the induction of probabilistic networks from data](https://scholariq.org/papers/a-bayesian-method-for-the-induction-of-probabilistic-networks-from-data-2/)
- [Decisions from Experience and the Effect of Rare Events in Risky Choice](https://scholariq.org/papers/decisions-from-experience-and-the-effect-of-rare-events-in-risky-choice/)
- [The BUGS Book: A Practical Introduction to Bayesian Analysis](https://scholariq.org/papers/the-bugs-book-a-practical-introduction-to-bayesian-analysis/)
- [Probabilistic decision-making under uncertainty for autonomous driving using continuous POMDPs](https://scholariq.org/papers/probabilistic-decision-making-under-uncertainty-for-autonomous-driving-using/)
- [A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP](https://scholariq.org/papers/a-tutorial-on-conducting-and-interpreting-a-bayesian-anova-in-jasp-2/)
- [A Bayesian Method for Constructing Bayesian Belief Networks from Databases](https://scholariq.org/papers/a-bayesian-method-for-constructing-bayesian-belief-networks-from-databases/)
- [Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process](https://scholariq.org/papers/automated-handwashing-assistance-for-persons-with-dementia-using-video-and-a/)
- [Distributed fusion in sensor networks](https://scholariq.org/papers/distributed-fusion-in-sensor-networks/)
- [Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning](https://scholariq.org/papers/learning-driver-behavior-models-from-traffic-observations-for-decision-making/)
- [A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments](https://scholariq.org/papers/a-probabilistic-model-for-estimating-driver-behaviors-and-vehicle-trajectories/)
- [The JASP Guidelines for Conducting and Reporting a Bayesian Analysis](https://scholariq.org/papers/the-jasp-guidelines-for-conducting-and-reporting-a-bayesian-analysis-2/)
- [Answering queries from context-sensitive probabilistic knowledge bases](https://scholariq.org/papers/answering-queries-from-context-sensitive-probabilistic-knowledge-bases/)
- [A survey on statistical methods for health care fraud detection](https://scholariq.org/papers/a-survey-on-statistical-methods-for-health-care-fraud-detection/)
## Topic primary papers
Showing 15 of 31.
- [A Bayesian Method for the Induction of Probabilistic Networks from Data](https://scholariq.org/papers/a-bayesian-method-for-the-induction-of-probabilistic-networks-from-data/)
- [A Bayesian method for the induction of probabilistic networks from data](https://scholariq.org/papers/a-bayesian-method-for-the-induction-of-probabilistic-networks-from-data-2/)
- [A Bayesian Method for Constructing Bayesian Belief Networks from Databases](https://scholariq.org/papers/a-bayesian-method-for-constructing-bayesian-belief-networks-from-databases/)
- [Distributed fusion in sensor networks](https://scholariq.org/papers/distributed-fusion-in-sensor-networks/)
- [A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments](https://scholariq.org/papers/a-probabilistic-model-for-estimating-driver-behaviors-and-vehicle-trajectories/)
- [The JASP Guidelines for Conducting and Reporting a Bayesian Analysis](https://scholariq.org/papers/the-jasp-guidelines-for-conducting-and-reporting-a-bayesian-analysis-2/)
- [Answering queries from context-sensitive probabilistic knowledge bases](https://scholariq.org/papers/answering-queries-from-context-sensitive-probabilistic-knowledge-bases/)
- [A FTA-based method for risk decision-making in emergency response](https://scholariq.org/papers/a-fta-based-method-for-risk-decision-making-in-emergency-response/)
- [Uncertainty theory as a basis for belief reliability](https://scholariq.org/papers/uncertainty-theory-as-a-basis-for-belief-reliability/)
- [Generating Bayesian Networks from Probability Logic Knowledge Bases](https://scholariq.org/papers/generating-bayesian-networks-from-probability-logic-knowledge-bases/)
- [Data association based on optimization in graphical models with application to sensor networks](https://scholariq.org/papers/data-association-based-on-optimization-in-graphical-models-with-application-to/)
- [Sensitivity analysis in multilinear probabilistic models](https://scholariq.org/papers/sensitivity-analysis-in-multilinear-probabilistic-models/)
- [Bayesian decision support for complex systems with many distributed experts](https://scholariq.org/papers/bayesian-decision-support-for-complex-systems-with-many-distributed-experts/)
- [The R Package stagedtrees for Structural Learning of Stratified Staged Trees](https://scholariq.org/papers/the-i-r-i-package-b-stagedtrees-b-for-structural-learning-of-stratified-staged/)
- [Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package](https://scholariq.org/papers/sensitivity-and-robustness-analysis-in-bayesian-networks-with-the-bnmonitor-r/)
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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.