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FineMorphs: Affine-diffeomorphic sequences for regression

arXiv 2305.17255 ↗First posted 26 May 2023stat.ML cs.LGcited by 0

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Abstract (arXiv)

A multivariate regression model of affine and diffeomorphic transformation sequences - FineMorphs - is presented. Leveraging concepts from shape analysis, model states are optimally "reshaped" by diffeomorphisms generated by smooth vector fields during learning. Affine transformations and vector fields are optimized within an optimal control setting, and the model can naturally reduce (or increase) dimensionality and adapt to large datasets via suboptimal vector fields. An existence proof of solution and necessary conditions for optimality for the model are derived. Experimental results on real datasets from the UCI repository are presented, with favorable results in comparison with state-of-the-art in the literature and densely-connected neural networks in TensorFlow.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 53 references that are in the map. First posted on arXiv 26 May 2023.

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References · 26

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