Dominic Boutet · @dominic_boutet
568 followers · 82 posts · Server neuromatch.social

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 or maybe 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!

#computationalneuroscience #decisionmaking #probabilisticgraphicalmodels #neuroscience #exactinference #variationalinference #causalinference #samplinginference #mcmc #parameterestimation #structurelearning #markovnetworks #bayesnetworks

Last updated 3 years ago