HIGHLIGHTS
- who: Streaming Variational Monte Carlo et al. from the (UNIVERSITY) have published the research work: Streaming Variational Monte Carlo, in the Journal: (JOURNAL)
- what: The authors develop a novel online learning framework leveraging inference and sequential which enables flexible and accurate Bayesian joint filtering. The authors propose a novel sequential Monte Carlo method for inferring a state-space model for the streaming time series scenario that adapts the proposal distribution onthe-fly by optimizing a surrogate lower bound to the log normalizer of the filtering distribution. The authors propose to combine sequential Monte Carlo and . . .
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