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Box particle filtering for nonlinear state estimation using interval analysis
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Constraints propagation techniques on intervals for a guaranteed localization using redundant data
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Interval Methods for Systems of Equations
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On sequential Monte Carlo sampling methods for Bayesian filtering
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Guaranteed non-linear estimation using constraint propagation on sets
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Sequential Imputations and Bayesian Missing Data Problems
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A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
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Particle filters for positioning, navigation, and tracking
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Particle filter based outdoor robot localization using natural features extracted from laser scanners
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Dynamic Vehicle Localization using Constraints Propagation Techniques on Intervals A comparison with Kalman Filtering
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Computing minimal-volume credible sets using interval analysis; application to bayesian estimation
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Subdivision Direction Selection in Interval Methods for Global Optimization
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Adapting the Sample Size in Particle Filters Through KLD-Sampling
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FastSLAM: a factored solution to the simultaneous localization and mapping problem
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Revising hull and box consistency
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Integral Algebra for Simulating Dynamical Systems with Interval Uncertaintiesdiv.Title { Font-Size: X-Large; Margin-Bottom: 1ex; Text-Align: Center; }
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Particle Filtering Combined with Interval Methods for Tracking Applications
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Particle Filtering Combined with Interval Methods for Tracking Applications
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Tuning of Extended Kalman Filter for nonlinear State Estimation
Editorial review for independent work. ICSAC — the Institute for Complexity
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