Probabilistic Graphical Models
Probabilistic graphical models for real decisions.
Bayesian networks, Markov networks, causal models, and the inference that runs on them. Worked examples across healthcare, retail, sports, policy, and drug discovery, every one shipping a model you can open and query in Darkstar.
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Latest
Causality APIs 42: Loyalty Offers And Customer Lifetime Value
A synthetic loyalty-offer model separates redemption from true customer value when identity resolution, prior loyalty, margin, personalization, churn, and reward liability interact.
Latest articles
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Causal modeling of over 41,000 drug molecules targeting breast cancer
In this post, we show that is possible to apply causal learning and inference to massive and high-dimensional data. We took to causal modeling of 207 molecular properties…
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Causal understanding of early detection of Autism Spectrum Disorder in toddlers
Discover the power of causality in early detection of autism spectrum disorder (ASD) in toddlers. Find out how it can enhance understanding and estimation.
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Drug Discovery with Causal Networks, Acetylecholinesterase (AChE)
Explore the role of causality in drug discovery. Discover how understanding the causal relationships between molecular features can optimize drug potency.