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- February 5–7, 2020, Singapore: Introductory Course
- February 10–12, 2020, Singapore: Advanced Course
- March 3–5, 2020, Al Ain, UAE: Introductory Course
- March 9–11, 2020, Al Ain, UAE: Advanced BayesiaLab Course
- March 24–26, 2020, Boston: Introductory Course
- April 7–9, 2020, Paris: Introductory Course
- May 6–8, 2020, Seattle: Introductory Course
- May 11–13, 2020, Seattle: Advanced Course
- June 15–17, 2020, Paris: Advanced Course
- October 5–7, 2020, Toronto: Introductory Course
- October 13–15, 2020, Toronto: Advanced Course

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Bayesian Networks for Judicial Reasoning - 2020 BayesiaLab Conference
- Archive: Previous BayesiaLab Conferences
- 2019 BayesiaLab Conference in Durham
- Carriger: A Bayesian network analysis of the Federal Employee Viewpoint Survey
- Girod: Limiting Vaccine Wastage by Optimizing Health System Support
- Hosseini: Integrated Markov Chain and Dynamic Bayesian Network Approach for Modeling Ripple Effect in Supply Chain
- Jouffe: Introducing BayesiaLab 9
- Keita: From Bayesian Networks to Cognitive Science
- Lasway: Predicting the Optimal Revisit Interval for Diabetic Patients
- MacDonald Gibson: Influence of Lead in Water on Lead in Children’s Blood
- Roostaei: Risk Analysis of PFAS Contamination in Private Water Wells
- Scott: Bayesian Structural Field Analysis of a Large Eddy Turbulent Flow Simulation Using Probabilistic Graphical Modeling
- Srikanth: Identifying Buying Groups at Customer Organizations using BayesiaLab
- Schulzke: Reasonable Certainty: Why Courts Should Use Bayesian Belief Networks to Estimate Economic Damages
- Smith & Hui: Bayesian Networks for Biological Discovery: Brains, Genes, and Ecosystems
- Thompson: Understanding Your Customer Through the 'Most Relevant Explanations' (MRE) Function in BayesiaLab
- Ulla: Knowledge Elicitation & Application
- Wilson: The Small Data Problem
- Zhang: Applying Bayesian Network Models to Fuse Information from Different Data Sources

- 2018 BayesiaLab Conference in Chicago
- Block: Using BayesiaLab in the Classroom — Experience of Teaching Marketing Mix Models
- Carrera: Large-Scale Inference for Intelligence Analysis
- Carriger: Conceptual Bayesian Networks for Supporting Contaminated Site Ecological Risk Assessments and Remediation Management
- Gard: Modern Approaches to Causal Modelling in Customer Experience Measurement
- Gora: A Framework for Engaging Non-Technical Stakeholders to Facilitate Bayesian Network Adoption
- Hammerslough & Singaraju: Unsupervised Bayesian Network Learning for Non-Obvious Marketing Insight
- Hubert: Natural Language Processing and Bayesian Networks
- Jouffe: Introducing BayesiaLab 8
- Kulkarni: Optimizing Mix of Local Media & Promotional Budgets for a Top 10-US Optical Retailer
- MacDonald Gibson: Methicillin-Resistant Staphylococcus aureus in Children Living with Industrial Hog Operation Workers
- McWilliams: Bayesian-Neural Networks Ensemble Modeling: An Initial Experiment
- Musson: Decision Support in Extreme Environments — Designing a Medical Care Support System for a Mission to Mars
- Scott: Phase Based Statistics from Direct Numerically Simulated Imagery of Sediment-Laden Oscillatory Flow for Bayesian Belief Network Analysis
- Sharrock: An Application of Bayesian Networks to Yield Prediction in Portuguese Viticulture
- Stoddard: Synthesis of Causal Discovery and Machine Learning—Questions Posed
- Thompson: Bayesian Sense-Making in Data Science
- Twardy: Crowdsourcing Bayesian Networks with Prediction Markets
- Wilson: Using Bayesian Networks to characterize habitat use by wildlife with data collected by remote cameras
- Xuereb Conti: Metamodeling with Bayesian Networks to Facilitate Intelligent Use of Engineering Simulation in Early Stages of Building Design
- Zhang: Sharpen Your Understanding of a Single Product or Consumer Segment Using Impact, Landscape and Profile Analysis

- 2017 BayesiaLab Conference in Paris
- Dr. Lionel Jouffe: Introducing BayesiaLab 7
- Prof. Philippe Weber: Bayesian Networks Application to the Dependability and the Control of Dynamic Systems
- Dr. Christophe Simon: Modeling Epistemic and Aleatory Uncertainty in Bayesian Networks for Dependability Analysis
- Gilles Debache: Why Recording No Findings? A Common Sample Selection Bias
- Stefan Conrady: Artificial Intelligence, Domain Knowledge, and Causal Inference
- Dr. Joanna Jaworska: Bayesian Integrated Testing Strategy (ITS) for Skin Sensitization Potency Assessment
- Marie Thomas: Evaluating the Link Between Microbiome and Cosmetic Clinical Signs
- Paolo Righetti: Bayesian Networks for Managing the Customer & Collaborator Experience
- Benoit Hubert: From Marketing Science to Artificial Intelligence with Bayesian Networks
- Hervé Tranger: Bayesian Networks in Market Research, from Exploration to Prescriptive Results
- Dr. Jacqueline MacDonald Gibson: Bayesian Network Models for Predicting Health Risks of Arsenic in Drinking Water
- Dr. Bart Jansen: Stroke Triage with Limited Information
- Dr. Steven Wilson: The Social Graph—Using Bayesian Networks to Identify Spatial Population Structuring Among Caribou in Subarctic Canada
- Dr. Olivier Cussenot: Bayesian Networks and Integrative Semiotic Models in Precision Medicine
- Dr. Alta de Waal: Spatially Discrete Probability Maps for Anti-Poaching Efforts
- Jean-François Collin: Risk Factor Analysis with Bayesian Networks in a Veterinary Epidemiological Study
- Erin Barr: Media Mix Optimization Using Bayesian Belief Networks and BayesiaLab

- 2016 BayesiaLab Conference in Nashville
- Dr. Roman Fomin: Modeling the Training Process of Olympic and Professional Athletes Using BayesiaLab
- Dr. Steve Wilson: Use of causal modeling with Bayesian networks to inform policy options for sustainable resource management
- Dr. Azizi Seixas: Lifestyle and Behavioral Determinants of Stroke Differences Between Blacks and Whites in the U.S.
- Dr. Cory Hutchinson: Using Bayesian Networks to identify and quantify factors affecting injury severity
- Sri Srikanth & Corey Sykes: Driving Digital Customer Engagement Powered by Bayesian Networks

- 2015 BayesiaLab Conference in Fairfax
- 2014 BayesiaLab Conference in Los Angeles
- 2013 BayesiaLab Conference in Orlando

- 2019 BayesiaLab Conference in Durham

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