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stat.ML2023
Fermat Distances: Metric Approximation, Spectral Convergence, and Clustering Algorithms
Nicolás García Trillos, Anna Little, Daniel McKenzie +1
We analyze the convergence properties of Fermat distances, a family of density-driven metrics defined on Riemannian manifolds with an associated probability measure. Fermat distanc…
cs.LG2023
It begins with a boundary: A geometric view on probabilistically robust learning
Leon Bungert, Nicolás García Trillos, Matt Jacobs +3
Although deep neural networks have achieved super-human performance on many classification tasks, they often exhibit a worrying lack of robustness towards adversarially generated e…