Pages that link to "Item:Q3526429"
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The following pages link to Bayesian spatio-temporal models based on discrete convolutions (Q3526429):
Displaying 12 items.
- A general science-based framework for dynamical spatio-temporal models (Q619127) (← links)
- Conditionally linear models for non-homogeneous spatial random fields (Q713950) (← links)
- Spatio-temporal modeling of global ozone data using convolution (Q2195527) (← links)
- Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling (Q2212505) (← links)
- Long-term time-dependent stochastic modelling of extreme waves (Q2331258) (← links)
- A Class of Convolution-Based Models for Spatio-Temporal Processes with Non-Separable Covariance Structure (Q3103140) (← links)
- Stationary space-time Gaussian fields and their time autoregressive representation (Q3153694) (← links)
- SPATIO-TEMPORAL MODELS FOR SOME DATA SETS IN CONTINUOUS SPACE AND DISCRETE TIME (Q3195189) (← links)
- Modelling zero-inflated spatio-temporal processes (Q4970902) (← links)
- Bayesian modeling of discrete-time point-referenced spatio-temporal data (Q6149602) (← links)
- A spatio-temporal model and inference tools for longitudinal count data on multicolor cell growth (Q6636176) (← links)
- Deep Latent Factor Model for Spatio-Temporal Forecasting (Q6637473) (← links)
