Eikonal depth: an optimal control approach to statistical depths

14 January 2022

Papers citing "Eikonal depth: an optimal control approach to statistical depths"

20 / 20 papers shown

Title
Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth Jeff Calder Mahmood Ettehad 88 16 0 17 Feb 2022
The Geometry of Adversarial Training in Binary Classification Leon Bungert Nicolas García Trillos Ryan W. Murray AAML 89 24 0 26 Nov 2021
Boundary Estimation from Point Clouds: Algorithms, Guarantees and Applications Jeff Calder Sangmin Park D. Slepčev 3DPC 74 10 0 05 Nov 2021
Distributionally Robust Learning Ruidi Chen I. Paschalidis OOD 80 67 0 20 Aug 2021
Large sample spectral analysis of graph-based multi-manifold clustering Nicolas García Trillos Pengfei He Chenghui Li 122 6 0 28 Jul 2021
Tukey Depths and Hamilton-Jacobi Differential Equations M. Molina-Fructuoso Ryan W. Murray 45 6 0 04 Apr 2021
Adversarial Classification: Necessary conditions and geometric flows Nicolas García Trillos Ryan W. Murray AAML 79 19 0 21 Nov 2020
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates Jeff Calder Brendan Cook Matthew Thorpe D. Slepčev 72 84 0 19 Jun 2020
Adversarial Risk via Optimal Transport and Optimal Couplings Muni Sreenivas Pydi Varun Jog 82 60 0 05 Dec 2019
A maximum principle argument for the uniform convergence of graph Laplacian regressors Nicolas García Trillos Ryan W. Murray 58 20 0 29 Jan 2019
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 90 319 0 23 Nov 2018
Halfspace depth does not characterize probability distributions Stanislav Nagy MDE 133 18 0 22 Oct 2018
Data depth and floating body Stanislav Nagy C. Schuett E. Werner MDE 134 42 0 28 Sep 2018
Error estimates for spectral convergence of the graph Laplacian on random geometric graphs towards the Laplace--Beltrami operator Nicolas García Trillos Moritz Gerlach Matthias Hein D. Slepčev 113 173 0 30 Jan 2018
Analysis of $p$ -Laplacian Regularization in Semi-Supervised Learning D. Slepčev Matthew Thorpe 57 115 0 19 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
A new analytical approach to consistency and overfitting in regularized empirical risk minimization Nicolas García Trillos Ryan W. Murray 36 21 0 01 Jul 2016
Monge-Kantorovich Depth, Quantiles, Ranks, and Signs Victor Chernozhukov Alfred Galichon Marc Hallin Marc Henry 191 244 0 29 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,145 0 20 Dec 2014
Continuum limit of total variation on point clouds Nicolás García Trillos D. Slepčev 3DPC 84 147 0 25 Mar 2014