Make uncertainty
understandable.
A visual Bayesian network and decision-analysis tool for teaching. Build a model, set the evidence, and see both the answer and the reasoning behind it.
TypeScriptReactExact inference
The engineering behind it
Variable elimination computes exact probabilities for discrete networks. Explain Mode measures each observation’s contribution by rerunning inference without it. A Web Worker handles larger networks; the interface reveals the arithmetic in layers.
The trade-off: exact inference supports inspectable results, but dense networks can become expensive. This is a teaching tool for discrete models, with explicit limits around multi-stage decisions and no parameter-learning claim.
A MODEL YOU CAN QUESTION. AN ANSWER YOU CAN EXPLAIN.
