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Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes

Structured Bayesian Networks: From Inference to Learning with Routes

AAAI 2019 · Probabilistic and scientific modeling › Uncertainty and Gaussian processes · approach: Approximate inference in Bayesian neural networks · 14 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use PSDD compilation instead of jointree sparse-table inferenceSBN exact inference (MPE) · SF map 10,500 edgesevaluation time (s): 607.294 -> 60.136Helped
use PSDD compilation instead of jointreeSBN exact inference · SF map 910 edgesevaluation time (s): 7.374 -> 2.223Helped
learn binary hmap with bottom-up matching heuristic instead of random hmapSBN route prediction · Route prediction, cabspottingDSN: 0.300 -> 0.250Helped
learn binary hmap with heuristic instead of randomSBN route prediction · Route prediction, cabspottingtrip length difference: 0.147 -> 0.076Helped
learn hmap with heuristic instead of randomSBN · Route prediction, cabspottingHausdorff distance: 0.120 -> 0.089Helped
learn hmap with heuristic instead of randomSBN · Route prediction, cabspottinginvalid routes (train / test): 3,833 / 59 -> 2,791 / 41Helped
use SBN with binary hmap classifier instead of logistic regression / naive BayesTaxi vs Google route classification · route classificationaccuracyHelped

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