#parameterestimation

I am taking a class on Probabilistic Graphical Models (PGMs) this semester and we have a final project which can be a breadth lit review on a topic or a research project.

Does anyone know about some cool work that combined PGM or PGM methods (e.g., inference, parameter estimation, learning with partial observations, etc.) with #ComputationalNeuroscience or maybe #DecisionMaking models? Ideally with a focus on methods, algorithms, or simulations.

I'm looking for some starting point to dig through the literature a bit and see if anything catches my attention.

Thanks in advance!

#ProbabilisticGraphicalModels #Neuroscience #ExactInference #VariationalInference #CausalInference #SamplingInference #MCMC #ParameterEstimation #StructureLearning #MarkovNetworks #BayesNetworks

#arxivfeed :

"Dynamic Bayesian Learning and Calibration of Spatiotemporal Mechanistic Systems"
https://arxiv.org/abs/2208.06528

#DynamicalSystems #ModelCalibration #Bayesian #ParameterEstimation #GaussianProcess