#bayesian inference
33 papers match
Maximum Likelihood and Bayesian Estimation for State-Space Models Using the Non-Gaussian Filter
Genshiro Kitagawa
The paper revisits deterministic non‑Gaussian filtering for nonlinear state‑space models, showing it can be used effectively for maximum likelihood and Bayesian estimation thanks t…
Bayesian Inference of Discretization Error Means in ODEs via Ensemble Kalman Filtering
Shoji Toyota, Yuto Miyatake
The paper introduces a Bayesian method that uses an Ensemble Kalman Filter to estimate the mean of discretization errors in ODE solvers, employing a Markov prior that reflects erro…
Bayesian Graphical Models under Positivity Constraints: A Scalable generalized likelihood Approach
Swarnali Raha, Partha Sarkar, Sirani Perera +1
The paper proposes a scalable Bayesian method for estimating precision matrices in Gaussian graphical models with total positivity constraints, using a D‑trace loss and spike‑and‑s…
Impact of numerical stability in Bayesian noise wave calibration on global 21-cm experiments
Saswata Dasgupta, Adarsh Kumar Dash, Dominic Anstey +3
The paper identifies and mitigates a numerical instability in the Bayesian noise‑wave calibration used for global 21‑cm experiments, improving reproducibility and accuracy of recei…
Bayesian Plackett--Luce latent block models for ranked data
Lapo Santi, Nial Friel, Valeria Vitelli
The paper proposes a Bayesian latent block model that jointly clusters assessors and items for ranked data using a Plackett–Luce observation model, with inference via Gibbs samplin…
Dynamic output-feedback stabilization of uncertain linear dynamics via digital twins
Philipp A. Guth, Karl Kunisch, Sergio S. Rodrigues +1
The paper proposes a digital‑twin framework that runs alongside an uncertain linear system, using real‑time data to estimate the system state and parameters while generating a stab…