🖥️2020 BayesiaLab Conference at the Laval Virtual World

October 26–30, 2020 — A Virtual Reality Event

The 8th Annual BayesiaLab Conference

Our first all-virtual BayesiaLab Conference at the Laval Virtual World was a great success! With nearly 200 registrations, we had more participants than ever. Despite time differences, researchers from British Columbia to Japan joined us in real time for the event. A big "thank you" to all who made this conference a success!

Conference Presentations

If you missed some of the talks, we uploaded recordings of all presentations and the corresponding slides.

🇫🇷pageIntroducing BayesiaLab 10🇨🇦pageLessons from Causal Analysis: Policy Implications for Woodland Caribou Recovery in Canada🇺🇸pageAssessing Coral Reef Condition Indicators for Local and Global Stressors Using Bayesian Networks🇫🇷pageBayesian Networks in the Context of Immunization Programs in Africa🇿🇦pageActivity-Based Travel Demand Generation Using Bayesian Networks🇺🇸pageThe Role of Internalizing and Externalizing Symptoms among Smokers and Physical Pain🇺🇸pageThe Role of Collider Bias in Understanding Statistics on Racially-Biased Policing🇺🇸pageBayesian Networks for Recommender Systems: Going Beyond Ratings Prediction🇺🇸pageQuantifying Cisco’s Mindshare to Guide Marketing Investment Decisions🇺🇸pageCybersecurity Risk Assessment with Bayesian Networks🇨🇭pageMonthly Sales & Operation Planning Process Mixing Economic Driver Forecast Uncertainty🇿🇦pageBayesian Networks for Knowledge Discovery and Curriculum Optimisation in Academic Programmes🇺🇸pageFrom Econometrics to Bayesian Network Analysis with BayesiaLab: Teaching and Applications🇺🇸pageModeling COVID-19 Business Interruption Insurance Claims Using Bayesian Networks🇮🇳pageCustomer Preference Sequencing for Better Customer Engagement🇺🇸pageIt's the Middle, Stupid! Machine Learning the Impact of Climate Risk Perceptions on Policy Support🇺🇸pageSpatio-temporal Multicomponent Optimal Learning State Estimation🇨🇦pageApplication of Bayesian Belief Networks to Evidence-Based Policy Development🇦🇺pageLearnings from the Application of Bayesian Networks and Dynamic Bayesian Networks to Fisheries Data