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Found 4 papers, 1 papers with code
Decentralized cooperative perception for autonomous vehicles: Learning to value the unknown
In particular, we propose Locally Predictable VAE (LP-VAE), which appears to be producing better belief states for predictions than state-of-the-art models, both as a standalone model and in the context of DRL.
Efficient exact computation of the conjunctive and disjunctive decompositions of D-S Theory for information fusion: Translation and extension
With it, we are able to reduce these computations up to a linear complexity in the number of focal sets in some cases.
Focal points and their implications for Möbius Transforms and Dempster-Shafer Theory
Dempster-Shafer Theory (DST) generalizes Bayesian probability theory, offering useful additional information, but suffers from a much higher computational burden.
Conservative, Proportional and Optimistic Contextual Discounting in the Belief Functions Theory
Information discounting plays an important role in the theory of belief functions and, generally, in information fusion.
