Author

Mitchell Ostrow

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#machine learning Sep 2026

Traversing the solution space of neural networks with Hessian Null Space Continuation

On a single task, deep neural networks can learn a wide range of solutions, depending on their optimizer, training data, architecture, and hyperparameters. Many of these solutions are surprisingly mode-connected: rather than isolated points in the weight space, they are connected by low loss regions. Despite this obser...

Ann C. Huang, Mitchell Ostrow, Zhou-Yang Lu et al. · arXiv.org · 0 citations

Open access Jul 2026

A metric for comparing complex systems by their dynamics

Comparisons are fundamental to science: experiment against model, one organism against another, a system against itself across time. Because many systems, from brains to climate, are characterized by how they evolve in time, it is a natural goal to compare their dynamics. Dynamical systems comparison is well defined, b...

Mitchell Ostrow, Adam J. Eisen, L. Kozachkov et al. · bioRxiv · 0 citations