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We introduce Dimple, a fully open-source API for probabilistic modeling. Dimple allows the user to specify probabilistic models in the form of graphical models, Bayesian networks, or factor graphs, and performs inference (by automatically deriving an inference engine from a variety of algorithms) on the model. Dimple also serves as a compiler for GP5, a(More)
  • Bill Bradley, Maj Carl Block, Maj Rich Chavez, Maj Phil Simonsen, Maj Tim Zadalis
  • 1996
Disclaimer 2025 is a study designed to comply with a directive from the chief of staff of the Air Force to examine the concepts, capabilities, and technologies the United States will require to remain the dominant air and space force in the future. Presented on 17 June 1996, this report was produced in the Department of Defense school environment of(More)
Efficient hardware implementations of statistical inference continue to grow in importance for a wide range of computing applications. While CPU cycles are increasingly being used for statistical inference, transistors are also becoming increasingly statistical. For implementing statistical algorithms, could it be that statistical electronic substrates are(More)
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