A neural Schrödinger-Föllmer diffusion, trained like the Path Integral Sampler, is repurposed as a global optimizer, with new conditional convergence bounds and competitive results on small tasks only.
A consensus-based global optimization method for high dimensional machine learning problems.ESAIM: Control, Optimisation and Calculus of Variations, 27:S5, 2021
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Path Integral Optimiser: Global Optimisation via Neural Schr\"odinger-F\"ollmer Diffusion
A neural Schrödinger-Föllmer diffusion, trained like the Path Integral Sampler, is repurposed as a global optimizer, with new conditional convergence bounds and competitive results on small tasks only.