4 citations · 11 across the 10 of their papers we have counts for
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cs.LG2023★ 1 cited
Learning Differentiable Particle Filter on the Fly
Jiaxi Li, Xiongjie Chen, Yunpeng Li
Differentiable particle filters are an emerging class of sequential Bayesian inference techniques that use neural networks to construct components in state space models. Existing a…
eess.SP2023
Differentiable Bootstrap Particle Filters for Regime-Switching Models
Wenhan Li, Xiongjie Chen, Wenwu Wang +2
Differentiable particle filters are an emerging class of particle filtering methods that use neural networks to construct and learn parametric state-space models. In real-world app…
cs.LG2023★ 1 cited
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference
Xiongjie Chen, Yunpeng Li
By approximating posterior distributions with weighted samples, particle filters (PFs) provide an efficient mechanism for solving non-linear sequential state estimation problems. W…