Publications

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2022

Feng, Jinchao; Maggioni, Mauro; Martin, Patrick; Zhong, Ming

Learning Interaction Variables and Kernels from Observations of Agent-Based Systems Inproceedings

In: IFAC Proceedings, 2022.

Abstract | Links | BibTeX | Tags: agent-based models, inverse problems, Machine learning, statistics

Popescu, Dan M.; Shade, Julie K.; Lai, Changxin; Aronis, Konstantinos N.; David Ouyang,; Moorthy, M. Vinayaga; Cook, Nancy R.; Lee, Daniel C.; Kadish, Alan; Albert, Christine M.; Wu, Katherine C.; Maggioni, Mauro; Trayanova, Natalia A.

Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart Journal Article

In: Nature Cardiovascular Research, 2022.

Links | BibTeX | Tags: Machine learning, medical imaging, neural networks

2021

Abramson, Haley G.; Popescu, Dan M.; Yu, Rebecca; Lai, Changxin; Shade, Julie K.; Wu, Katherine C.; Maggioni, Mauro; Trayanova, Natalia A.

Anatomically-Informed Deep Learning on Contrast-Enhanced Cardiac MRI for Scar Segmentation and Clinical Feature Extraction Journal Article

In: Cardiovascular Digital Health Journal, 2021.

Links | BibTeX | Tags: imaging, Machine learning, medical imaging

Zhong, Ming; Miller, Jason; Maggioni, Mauro

Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides Unpublished

2021.

Links | BibTeX | Tags: agent-based models, interacting particle systems, Machine learning

Liao, Wenjing; Maggioni, Mauro; Vigogna, Stefano

Multiscale regression on intrinsically low-dimensional sets Journal Article

In: Mathematics in Engineering, vol. 4, no. 4, 2021.

Links | BibTeX | Tags: Machine learning, Manifold Learning, statistics, supervised learning

Sichen Yang Felix X.-F. Ye, Mauro Maggioni

Nonlinear model reduction for slow-fast stochastic systems near manifolds Journal Article

In: 2021.

Abstract | Links | BibTeX | Tags: inverse problems, Machine learning, Manifold Learning, model reduction, random walks, statistics, stochastic systems

Mauro Maggioni Fei Lu, Sui Tang

Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories Journal Article

In: Foundation of Computational Mathematics, 2021.

Abstract | Links | BibTeX | Tags: agent-based models, interacting particle systems, Machine learning, statistics, stochastic systems

Lu, Fei; Li, Zhongyang; Maggioni, Mauro; Tang, Sui; Zhang, Cheng

On the identifiability of interaction functions in systems of interacting particles Journal Article

In: Stochastic Processes and their Applications, vol. 132, 2021.

Links | BibTeX | Tags: agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics

Jason Miller Mauro Maggioni, Hongda Qiu

Learning Interaction Kernels for Agent Systems on Riemannian Manifolds Proceeding

ICML, 2021.

Abstract | Links | BibTeX | Tags: agent-based models, interacting particle systems, Machine learning, model reduction, statistics

Mauro Maggioni Fei Lu, Sui Tang

Learning interaction kernels in heterogeneous systems of agents from multiple trajectories Journal Article

In: Journ. Mach. Learn. res., vol. 2, no. 32, pp. 1–67, 2021.

Abstract | Links | BibTeX | Tags: Active Learning, interacting particle systems, inverse problems, Machine learning

2020

Sui Tang Jason Miller, Ming Zhong

Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems Online Forthcoming

Forthcoming.

Links | BibTeX | Tags: agent-based models, interacting particle systems, inverse problems, Machine learning

Tomita, Tyler M; Browne, James; Shen, Cencheng; Chung, Jaewon; Patsolic, Jesse L; Falk, Benjamin; Priebe, Carey E; Yim, Jason; Burns, Randal; Maggioni, Mauro; Vogelstein, Joshua T

Sparse Projection Oblique Randomer Forests Journal Article

In: Journal of Machine Learning Research, vol. 21, no. 104, pp. 1-39, 2020.

Links | BibTeX | Tags: Machine learning, statistics, supervised learning

2019

Maggioni, Mauro; Miller, Jason; Zhong, Ming

Data-driven Discovery of Emergent Behaviors in Collective Dynamics Journal Article

In: Physica D: Nonlinear Phenomena, 2019.

Links | BibTeX | Tags: agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics

Little, Anna V; Maggioni, Mauro; Murphy, James M

Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms Journal Article

In: Journ. Mach. Learn. Res., vol. 21, pp. 1-66, 2019.

Links | BibTeX | Tags: Clustering, diffusion geometry, Machine learning, Unsupervised Learning

Browne, James Tomita Tyler M.; Shen, Cencheng; Chung, Jaewon; Patsolic, Jesse L; Falk, Benjamin; Priebe, Carey E Yim Jason; RandalMaggioni, Mauro Burns; Vogelstein, Joshua T

Sparse Projection Oblique Randomer Forests Journal Article

In: Journ. Mach. Learn. Res., 2019.

Links | BibTeX | Tags: Machine learning, statistics, supervised learning

Maggioni, Mauro; Murphy, James M

Learning by active nonlinear diffusion Journal Article

In: Foundations of Data Science, vol. 1, no. “2639-8001-2019-3-271”, pp. 271, 2019, ISSN: A0000-0002.

Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, Machine learning, Unsupervised Learning

Lu, Fei; Zhong, Ming; Tang, Sui; Maggioni, Mauro

Nonparametric inference of interaction laws in systems of agents from trajectory data Journal Article

In: Proceedings of the National Academy of Sciences, vol. 116, no. 29, pp. 14424–14433, 2019, ISSN: 0027-8424.

Links | BibTeX | Tags: agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics

Vogelstein, Joshua T; Bridgeford, Eric W; Wang, Qing; Priebe, Carey E; Maggioni, Mauro; Shen, Cencheng

Discovering and deciphering relationships across disparate data modalities Journal Article

In: eLife, pp. 8:e41690, 2019.

Links | BibTeX | Tags: Machine learning, statistics, Unsupervised Learning

Liao, Wenjing; Maggioni, Mauro

Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data Journal Article

In: Journal of machine learning Research, vol. 20, no. 98, pp. 1-63, 2019.

Links | BibTeX | Tags: geometric wavelets, Machine learning, multiscale analysis, statistics

2018

Murphy, James M; Maggioni, Mauro

Iterative Active Learning with Diffusion Geometry for Hyperspectral Images Inproceedings

In: Proc. of WHISPERS, 2018.

Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning

Murphy, James M; Maggioni, Mauro

Diffusion geometric methods for fusion of remotely sensed data Inproceedings

In: Velez-Reyes, Miguel; Messinger, David W (Ed.): Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, pp. 137 – 147, International Society for Optics and Photonics SPIE, 2018.

Links | BibTeX | Tags: Active Learning, Clustering, diffusion geometry, hyperspectral imaging, imaging, Machine learning, Unsupervised Learning

2017

Crosskey, Miles C; Maggioni, Mauro

ATLAS: A geometric approach to learning high-dimensional stochastic systems near manifolds Journal Article

In: Journal of Multiscale Modeling and Simulation, vol. 15, no. 1, pp. 110–156, 2017, (arxiv: 1404.0667).

Links | BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, statistics, stochastic systems

Tomita, Tyler M; Maggioni, Mauro; Vogelstein, Joshua T

ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations Inproceedings

In: SIAM Data Mining, 2017.

BibTeX | Tags: Machine learning, statistics, supervised learning

Tomita, Tyler; Maggioni, Mauro; Vogelstein, Joshua T

ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations Inproceedings

In: 2017.

BibTeX | Tags: Machine learning, statistics, supervised learning

Little, Anna V; Maggioni, Mauro; Rosasco, Lorenzo

Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature Journal Article

In: Applied and Computational Harmonic Analysis, vol. 43, no. 3, pp. 504 – 567, 2017, (Submitted: 2012, MIT-CSAIL-TR-2012-029/CBCL-310).

BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, statistics

2016

Shen, Cencheng; Priebe, Carey E; Maggioni, Mauro; Vogelstein, Joshua T

Dependence Discovery from Multimodal Data via Multiscale Generalized Correlation Journal Article

In: Submitted, 2016.

BibTeX | Tags: Machine learning, statistics, Unsupervised Learning

Yin, Rachel; Monson, Eric; Honig, Elisabeth; Daubechies, Ingrid; Maggioni, Mauro

Object recognition in art drawings: Transfer of a neural network Inproceedings

In: Proc. IEEE ICASSP, 2016.

BibTeX | Tags: imaging, Machine learning, neural networks, transfer learning

Bongini, Mattia; Fornasier, Massimo; Hansen, M; Maggioni, Mauro

Inferring Interaction Rules From Observations of Evolutive Systems I: The Variational Approach journal

2016.

Links | BibTeX | Tags: agent-based models, interacting particle systems, Machine learning, statistics

Liao, Wenjing; Maggioni, Mauro; Vigogna, S

Learning adaptive multiscale approximations to data and functions near low-dimensional sets Inproceedings

In: Proceedings of the IEEE Information Theory Workshop, 2016, (Cambridge, UK).

BibTeX | Tags: Machine learning, Manifold Learning, statistics, supervised learning

2015

Tomita, Tyler M; Maggioni, Mauro; Vogelstein, Joshua T

Randomer Forests Journal Article

In: arXiv preprint arXiv:1506.03410, 2015.

Links | BibTeX | Tags: Machine learning, statistics, supervised learning

2013

Gerber, S; Maggioni, Mauro

Multiscale dictionaries, transforms, and learning in high-dimensions Inproceedings

In: Proc. SPIE conference Optics and Photonics, 2013.

BibTeX | Tags: dictionary learning, imaging, Machine learning, multiscale analysis

Iwen, Mark A; Maggioni, Mauro

Approximation of points on low-dimensional manifolds via random linear projections Journal Article

In: Inference and Information, vol. 2, no. 1, pp. 1–31, 2013, (arXiv:1204.3337v1, 2012).

BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis

2012

Chen, Guangliang; Iwen, Mark A; Chin, Peter S; Maggioni, Mauro

A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements Inproceedings

In: Visual Communications and Image Processing (VCIP), 2012 IEEE, pp. 1-6, 2012.

BibTeX | Tags: Clustering, diffusion geometry, Machine learning, Unsupervised Learning

Bouvrie, Jake; Maggioni, Mauro

Geometric Multiscale Reduction for Autonomous and Controlled Nonlinear Systems Inproceedings

In: IEEE Conference on Decision and Control (CDC), 2012.

BibTeX | Tags: control theory, geometric wavelets, Machine learning, multiscale analysis

Bouvrie, Jake; Maggioni, Mauro

Efficient Solution of Markov Decision Problems with Multiscale Representations Inproceedings

In: Proc. 50th Annual Allerton Conference on Communication, Control, and Computing, 2012.

BibTeX | Tags: Machine learning, reinforcement learning, representation learning

Bouvrie, Jake; Maggioni, Mauro

Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning Journal Article

In: 2012.

Links | BibTeX | Tags: Machine learning, multiscale analysis, reinforcement learning, representation learning, spectral graph theory, transfer learning

Chen, Guangliang; Iwen, Mark A; Chin, Peter S; Maggioni, Mauro

A Fast Multiscale Framework for Data in High Dimensions: Measure Estimation, Anomaly Detection, and Compressive Measurements Inproceedings

In: Visual Communications and Image Processing (VCIP), 2012 IEEE, pp. 1-6, 2012.

Links | BibTeX | Tags: Clustering, diffusion geometry, Machine learning, Unsupervised Learning

Allard, William K; Chen, Guangliang; Maggioni, Mauro

Multi-scale geometric methods for data sets II: Geometric Multi-Resolution Analysis Journal Article

In: Applied and Computational Harmonic Analysis, vol. 32, no. 3, pp. 435–462, 2012.

BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, statistics

2011

Chen, Guangliang; Little, Anna V; Maggioni, Mauro

Multi-Resolution Geometric Analysis for data in high dimensions Journal Article

In: Proc. FFT 2011, 2011.

BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis

Maggioni, Mauro

Multiscale Geometric Dictionaries for Point-Cloud Data, Presented at SPARS 11, http://www.math.duke.edu/~mauro/research.html#Talks Journal Article

In: 2011, (Presented at SPARS 11).

Links | BibTeX | Tags: dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis

Zheng, W; Rohrdanz, M A; Maggioni, Mauro; Clementi, Cecilia

Polymer reversal rate calculated via locally scaled diffusion map Journal Article

In: J. Chem. Phys., no. 134, pp. 144108, 2011.

BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems

Rohrdanz, M A; Zheng, W; Maggioni, Mauro; Clementi, Cecilia

Determination of reaction coordinates via locally scaled diffusion map Journal Article

In: J. Chem. Phys., no. 134, pp. 124116, 2011.

BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems

Chen, Guangliang; Maggioni, Mauro

Multiscale Geometric Dictionaries for Point-Cloud Data Inproceedings

In: Proc. SampTA, 2011.

BibTeX | Tags: dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis

Chen, Guangliang; Maggioni, Mauro

Multiscale Geometric and Spectral Analysis of Plane Arrangements Inproceedings

In: Conference on Computer Vision and Pattern Recognition, 2011.

BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis

2010

Chen, Guangliang; Maggioni, Mauro

Multiscale Geometric Methods for Data Sets III: multiple planes Journal Article

In: in preparation, 2010.

BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics

Chen, Guangliang; Maggioni, Mauro

Multiscale Geometric Wavelets for the Analysis of Point Clouds Journal Article

In: Proc. CISS 2010, 2010.

BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, spectral graph theory

2009

Little, Anna V; Jung, Y -M; Maggioni, Mauro

Multiscale Estimation of Intrinsic Dimensionality of Data Sets Inproceedings

In: Proc. A.A.A.I., 2009.

BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics

Little, Anna V; Lee, J; Jung, Y -M; Maggioni, Mauro

Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale $SVD$ Inproceedings

In: Proc. S.S.P., 2009.

BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics

2008

Szlam, Arthur D; Maggioni, Mauro; Coifman, Ronald R

Regularization on Graphs with Function-adapted Diffusion Processes Journal Article

In: Jour. Mach. Learn. Res., no. 9, pp. 1711–1739, 2008, ((YALE/DCS/TR1365, Yale Univ, July 2006)).

BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, random walks, semisupervised learning, 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

In: SIAM J.M.M.S., vol. 7, no. 2, pp. 842–864, 2008.

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

71 entries « 1 of 2 »
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