Research map / Probabilistic and scientific modeling / Variational and generative sampling
Amortized Variational Transdimensional Inference
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Extends flow-based stochastic variational inference to transdimensional Bayesian inference over joint model and parameter spaces.
Problem
Flow-based stochastic variational inference has been limited to fixed-dimensional parameter spaces, whereas multi-model Bayesian inference requires transdimensional joint model and parameter spaces.
Approach
Applies amortized flow-based variational inference to transdimensional problems, extending SVI from a fixed-dimensional to a joint model-and-parameter space.
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