2 papers
stat.CO2026
Truncated Neural Likelihood Estimation for Simulation-Based Inference in State-Space Models
Kostas Tsampourakis, VÃctor Elvira
State-space models (SSMs) are powerful probabilistic tools for modeling time-varying systems with latent dynamics. Inference in SSMs involves the estimation of latent states and pa…
stat.CO2026
A Gaussian Sum Filter for Unifying Gaussian and Particle Filters
Kostas Tsampourakis, VÃctor Elvira
State-space models (SSMs) are a broad class of probabilistic models for dynamical systems with many applications in engineering and science. Bayesian filtering is analytically trac…