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We propose a novel approach to sequential Bayesian inference based on variational Bayes (VB).
A useful theorem for nonlinear devices having gaussian inputs
Robert Price · 1958
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On diagonal approximations to the extended kalman filter for online training of bayesian neural networks
Peter G Chang, Kevin Patrick Murphy, and Matt Jones · 2022
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An optimization-centric view on bayes’ rule: Reviewing and generalizing variational inference
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Implicit maximum a posteriori filtering via adaptive optimization
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Low-rank extended Kalman filtering for online learning of neural networks from streaming data
Peter G Chang, Gerardo Durán-Martín, Alexander Y Shestopaloff, Matt Jones, and Kevin Murphy · 2023
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