Publications

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2020

Okada, David Jason Miller; Jonathan Chrispin; Adityo Prakosa; Natalia Trayanova; Steven Jones; Mauro Maggioni; Katherine Wu David R ; C R

Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients with Ischemic Cardiomyopathy Journal Article

Circulation: Arrhythmia and Electrophysiology, 2020.

Links | BibTeX | Tags: imaging, Laplacian eigenfunctions, medical imaging

2010

Jones, Peter W; Maggioni, Mauro; Schul, Raanan

Universal local manifold parametrizations via heat kernels and eigenfunctions of the Laplacian Journal Article

Ann. Acad. Scient. Fen., 35 , pp. 1–44, 2010, (http://arxiv.org/abs/0709.1975).

BibTeX | Tags: diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory

2008

Coifman, Ronald R; Maggioni, Mauro

Geometry Analysis and Signal Processing on Digital Data, Emergent Structures, and Knowledge Building Miscellaneous

SIAM News, 2008.

BibTeX | Tags: diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory

Maggioni, Mauro; Mhaskar, Hrushikesh

Diffusion polynomial frames on metric measure spaces Journal Article

ACHA, 3 , pp. 329–353, 2008.

BibTeX | Tags: approximation theory, diffusion geometry, heat kernels, Laplacian eigenfunctions, multiscale analysis

Jones, Peter W; Maggioni, Mauro; Schul, Raanan

Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels Journal Article

Proc. Nat. Acad. Sci., 105 (6), pp. 1803–1808, 2008.

BibTeX | Tags: diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory

Coifman, Ronald R; Kevrekidis, Ioannis G; Lafon, Stephane; Maggioni, Mauro; Nadler, Boaz

Diffusion Maps, reduction coordinates and low dimensional representation of stochastic systems Journal Article

SIAM J.M.M.S., 7 (2), pp. 842–864, 2008.

BibTeX | Tags: diffusion geometry, dynamical systems, Laplacian eigenfunctions, Machine learning, model reduction, stochastic systems

2007

Mahadevan, Sridhar; Maggioni, Mauro

Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes Journal Article

JMLR, 8 , pp. 2169–2231, 2007.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

2006

Coifman, Ronald R; Lafon, Stephane; Maggioni, Mauro; Keller, Y; Szlam, A D; Warner, F J; Zucker, S W

Geometries of sensor outputs, inference, and information processing Inproceedings

Athale, John Zolper; Eds. Intelligent Integrated Microsystems; Ravindra C A (Ed.): Proc. SPIE, pp. 623209, 2006.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems

Maggioni, Mauro; Mahadevan, Sridhar

Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes Inproceedings

ICML 2006, pp. 601–608, 2006.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

Mahadevan, Sridhar; Ferguson, Kim; Osentoski, Sarah; Maggioni, Mauro

Simultaneous Learning of Representation and Control In Continuous Domains Inproceedings

AAAI, AAAI Press, 2006.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

2005

Coifman, Ronald R; Maggioni, Mauro; Zucker, Steven W; Kevrekidis, Ioannis G

Geometric diffusions for the analysis of data from sensor networks Journal Article

Curr Opin Neurobiol, 15 (5), pp. 576–84, 2005.

BibTeX | Tags: diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems

Mahadevan, Sridhar; Maggioni, Mauro

Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions Inproceedings

University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005, 2005.

BibTeX | Tags: diffusion geometry, diffusion wavelets, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory

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