Novel Approach to Multi-Modal Inference with Normalizing Flows

This research introduces a method for amortized inference in multi-modal scenarios using likelihood-weighted normalizing flows. The approach is likely significant for applications requiring complex probabilistic modeling and uncertainty quantification across various data modalities.