A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Functional adapts to graph structures for machine learning applications.
We study global Mumford-Shah minimizers in , introduced by Bonnet as blow-up limits of Mumford-Shah minimizers. We prove a new monotonicity formula for the energy of when the singular set is contained in a smooth enough cone. We then use this monotonicity to prove that for any reduced global minimizer $(u…
Proposes a new loss function for deep learning image segmentation.
The Perona-Malik model has been very successful at restoring images from noisy input. In this paper, we reinterpret the Perona-Malik model in the language of Gaussian scale mixtures and derive some extensions of the model. Specifically, we show that the expectation-maximization (EM) algorithm applied to Gaussian scale …