## 2011 |

Zheng, W; Rohrdanz, M A; Maggioni, Mauro; Clementi, Cecilia Polymer reversal rate calculated via locally scaled diffusion map Journal Article J. Chem. Phys., (134), pp. 144108, 2011. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems @article{ZRMC:PolymerReversal, title = {Polymer reversal rate calculated via locally scaled diffusion map}, author = {W Zheng and M A Rohrdanz and Mauro Maggioni and Cecilia Clementi}, year = {2011}, date = {2011-01-01}, journal = {J. Chem. Phys.}, number = {134}, pages = {144108}, keywords = {diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

Rohrdanz, M A; Zheng, W; Maggioni, Mauro; Clementi, Cecilia Determination of reaction coordinates via locally scaled diffusion map Journal Article J. Chem. Phys., (134), pp. 124116, 2011. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems @article{RZMC:ReactionCoordinatesLocalScaling, title = {Determination of reaction coordinates via locally scaled diffusion map}, author = {M A Rohrdanz and W Zheng and Mauro Maggioni and Cecilia Clementi}, year = {2011}, date = {2011-01-01}, journal = {J. Chem. Phys.}, number = {134}, pages = {124116}, keywords = {diffusion geometry, Machine learning, Manifold Learning, molecular dynamics, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

Chen, Guangliang; Maggioni, Mauro Multiscale Geometric Dictionaries for Point-Cloud Data Inproceedings Proc. SampTA, 2011. BibTeX | Tags: dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis @inproceedings{CM:SamptaGW, title = {Multiscale Geometric Dictionaries for Point-Cloud Data}, author = {Guangliang Chen and Mauro Maggioni}, year = {2011}, date = {2011-01-01}, booktitle = {Proc. SampTA}, keywords = {dictionary learning, geometric wavelets, Machine learning, Manifold Learning, multiscale analysis}, pubstate = {published}, tppubtype = {inproceedings} } |

Chen, Guangliang; Maggioni, Mauro Multiscale Geometric and Spectral Analysis of Plane Arrangements Inproceedings Conference on Computer Vision and Pattern Recognition, 2011. BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis @inproceedings{CM:CVPR2011, title = {Multiscale Geometric and Spectral Analysis of Plane Arrangements}, author = {Guangliang Chen and Mauro Maggioni}, year = {2011}, date = {2011-01-01}, booktitle = {Conference on Computer Vision and Pattern Recognition}, keywords = {Machine learning, Manifold Learning, multiscale analysis}, pubstate = {published}, tppubtype = {inproceedings} } |

## 2010 |

Monson, Eric; Chen, Guangliang; Brady, Rachel; Maggioni, Mauro Data representation and exploration with Geometric Wavelets Inproceedings Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium, pp. 243–244, 2010. Links | BibTeX | Tags: geometric wavelets, visualization @inproceedings{MM:Vast2010, title = {Data representation and exploration with Geometric Wavelets}, author = {Eric Monson and Guangliang Chen and Rachel Brady and Mauro Maggioni}, doi = {10.1109/VAST.2010.5653822}, year = {2010}, date = {2010-12-01}, booktitle = {Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium}, pages = {243–244}, keywords = {geometric wavelets, visualization}, pubstate = {published}, tppubtype = {inproceedings} } |

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 @article{jms:UniformizationEigenfunctions2, title = {Universal local manifold parametrizations via heat kernels and eigenfunctions of the Laplacian}, author = {Peter W Jones and Mauro Maggioni and Raanan Schul}, year = {2010}, date = {2010-01-01}, journal = {Ann. Acad. Scient. Fen.}, volume = {35}, pages = {1–44}, note = {http://arxiv.org/abs/0709.1975}, keywords = {diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory}, pubstate = {published}, tppubtype = {article} } |

Guinney, J; Febbo, P; Maggioni, Mauro; Mukherjee, S Multiscale factor models for molecular networks Journal Article Proc. JSM, 2010. BibTeX | Tags: spectral clustering @article{GFMS:MultiscaleMolecularNetworks, title = {Multiscale factor models for molecular networks}, author = {J Guinney and P Febbo and Mauro Maggioni and S Mukherjee}, year = {2010}, date = {2010-01-01}, journal = {Proc. JSM}, keywords = {spectral clustering}, pubstate = {published}, tppubtype = {article} } |

Chen, Guangliang; Maggioni, Mauro Multiscale Geometric Methods for Data Sets III: multiple planes Journal Article in preparation, 2010. BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics @article{CM:MGM3, title = {Multiscale Geometric Methods for Data Sets III: multiple planes}, author = {Guangliang Chen and Mauro Maggioni}, year = {2010}, date = {2010-01-01}, journal = {in preparation}, keywords = {Machine learning, Manifold Learning, multiscale analysis, statistics}, pubstate = {published}, tppubtype = {article} } |

Chen, Guangliang; Maggioni, Mauro Multiscale Geometric Wavelets for the Analysis of Point Clouds Journal Article Proc. CISS 2010, 2010. BibTeX | Tags: geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, spectral graph theory @article{CM:geometricwaveletsciss, title = {Multiscale Geometric Wavelets for the Analysis of Point Clouds}, author = {Guangliang Chen and Mauro Maggioni}, year = {2010}, date = {2010-01-01}, journal = {Proc. CISS 2010}, keywords = {geometric wavelets, Machine learning, Manifold Learning, multiscale analysis, spectral graph theory}, pubstate = {published}, tppubtype = {article} } |

Monson, Eric; Chen, Guangliang; Brady, Rachel; Maggioni, Mauro Data Representation and Exploration with Geometric Wavelets Inproceedings Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST), 2010. BibTeX | Tags: geometric wavelets, visualization @inproceedings{Monson:VAST2010, title = {Data Representation and Exploration with Geometric Wavelets}, author = {Eric Monson and Guangliang Chen and Rachel Brady and Mauro Maggioni}, year = {2010}, date = {2010-01-01}, booktitle = {Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST)}, keywords = {geometric wavelets, visualization}, pubstate = {published}, tppubtype = {inproceedings} } |

## 2009 |

Little, Anna V; Jung, Y -M; Maggioni, Mauro Multiscale Estimation of Intrinsic Dimensionality of Data Sets Inproceedings Proc. A.A.A.I., 2009. BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics @inproceedings{MM:MultiscaleDimensionalityEstimationAAAI, title = {Multiscale Estimation of Intrinsic Dimensionality of Data Sets}, author = {Anna V Little and Y -M Jung and Mauro Maggioni}, year = {2009}, date = {2009-01-01}, booktitle = {Proc. A.A.A.I.}, keywords = {Machine learning, Manifold Learning, multiscale analysis, statistics}, pubstate = {published}, tppubtype = {inproceedings} } |

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 Proc. S.S.P., 2009. BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, statistics @inproceedings{MM:MultiscaleDimensionalityEstimationSSP, title = {Estimation of intrinsic dimensionality of samples from noisy low-dimensional manifolds in high dimensions with multiscale $SVD$}, author = {Anna V Little and J Lee and Y -M Jung and Mauro Maggioni}, year = {2009}, date = {2009-01-01}, booktitle = {Proc. S.S.P.}, keywords = {Machine learning, Manifold Learning, multiscale analysis, statistics}, pubstate = {published}, tppubtype = {inproceedings} } |

Willinger, Walter; Rejaie, Reza; Torkjazi, M; Valafar, M; Maggioni, Mauro Research on Online Social Networks: Time to Face the Real Challenges Inproceedings Proc. 2nd Workshop on Hot Topics in Measurement and Modeling of Computer Systems (HotMetrics’09), 2009. BibTeX | Tags: @inproceedings{wrm:OnlineSocial, title = {Research on Online Social Networks: Time to Face the Real Challenges}, author = {Walter Willinger and Reza Rejaie and M Torkjazi and M Valafar and Mauro Maggioni}, year = {2009}, date = {2009-01-01}, booktitle = {Proc. 2nd Workshop on Hot Topics in Measurement and Modeling of Computer Systems (HotMetrics’09)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |

## 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 @misc{CM:SiamNews, title = {Geometry Analysis and Signal Processing on Digital Data, Emergent Structures, and Knowledge Building}, author = {Ronald R Coifman and Mauro Maggioni}, year = {2008}, date = {2008-11-01}, howpublished = {SIAM News}, keywords = {diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory}, pubstate = {published}, tppubtype = {misc} } |

Szlam, Arthur D; Maggioni, Mauro; Coifman, Ronald R Regularization on Graphs with Function-adapted Diffusion Processes Journal Article Jour. Mach. Learn. Res., (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 @article{SMC:GeneralFrameworkAdaptiveRegularization, title = {Regularization on Graphs with Function-adapted Diffusion Processes}, author = {Arthur D Szlam and Mauro Maggioni and Ronald R Coifman}, year = {2008}, date = {2008-08-01}, journal = {Jour. Mach. Learn. Res.}, number = {9}, pages = {1711–1739}, note = {(YALE/DCS/TR1365, Yale Univ, July 2006)}, keywords = {diffusion geometry, Machine learning, Manifold Learning, random walks, semisupervised learning, spectral graph theory}, pubstate = {published}, tppubtype = {article} } |

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 @article{MM:DiffusionPolynomialFrames, title = {Diffusion polynomial frames on metric measure spaces}, author = {Mauro Maggioni and Hrushikesh Mhaskar}, year = {2008}, date = {2008-05-01}, journal = {ACHA}, volume = {3}, pages = {329–353}, keywords = {approximation theory, diffusion geometry, heat kernels, Laplacian eigenfunctions, multiscale analysis}, pubstate = {published}, tppubtype = {article} } |

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 @article{jms:UniformizationEigenfunctions, title = {Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels}, author = {Peter W Jones and Mauro Maggioni and Raanan Schul}, year = {2008}, date = {2008-02-01}, journal = {Proc. Nat. Acad. Sci.}, volume = {105}, number = {6}, pages = {1803–1808}, keywords = {diffusion geometry, heat kernels, Laplacian eigenfunctions, Manifold Learning, multiscale analysis, random walks, spectral graph theory}, pubstate = {published}, tppubtype = {article} } |

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 @article{CKLMN:DiffusionMapsReductionCoordinates, title = {Diffusion Maps, reduction coordinates and low dimensional representation of stochastic systems}, author = {Ronald R Coifman and Ioannis G Kevrekidis and Stephane Lafon and Mauro Maggioni and Boaz Nadler}, year = {2008}, date = {2008-01-01}, journal = {SIAM J.M.M.S.}, volume = {7}, number = {2}, pages = {842–864}, keywords = {diffusion geometry, dynamical systems, Laplacian eigenfunctions, Machine learning, model reduction, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

## 2007 |

Coifman, Ronald R; Maggioni, Mauro Multiscale Data Analysis with Diffusion Wavelets Journal Article Proc. SIAM Bioinf. Workshop, Minneapolis, 2007. BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems @article{CM:MsDataDiffWavelets, title = {Multiscale Data Analysis with Diffusion Wavelets}, author = {Ronald R Coifman and Mauro Maggioni}, year = {2007}, date = {2007-04-01}, journal = {Proc. SIAM Bioinf. Workshop, Minneapolis}, keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

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 @article{smmm:jmrl1, title = {Proto-value Functions: A Spectral Framework for Solving Markov Decision Processes}, author = {Sridhar Mahadevan and Mauro Maggioni}, year = {2007}, date = {2007-01-01}, journal = {JMLR}, volume = {8}, pages = {2169–2231}, keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory}, pubstate = {published}, tppubtype = {article} } |

## 2006 |

Coifman, Ronald R; Maggioni, Mauro Diffusion Wavelets Journal Article Appl. Comp. Harm. Anal., 21 (1), pp. 53–94, 2006, ((Tech. Rep. YALE/DCS/TR-1303, Yale Univ., Sep. 2004)). BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems @article{CMDiffusionWavelets, title = {Diffusion Wavelets}, author = {Ronald R Coifman and Mauro Maggioni}, year = {2006}, date = {2006-07-01}, journal = {Appl. Comp. Harm. Anal.}, volume = {21}, number = {1}, pages = {53–94}, note = {(Tech. Rep. YALE/DCS/TR-1303, Yale Univ., Sep. 2004)}, keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

Bremer, James Jr. C; Coifman, Ronald R; Maggioni, Mauro; Szlam, Arthur D Diffusion Wavelet Packets Journal Article Appl. Comp. Harm. Anal., 21 (1), pp. 95–112, 2006, ((Tech. Rep. YALE/DCS/TR-1304, 2004)). BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems @article{DiffusionWaveletPackets, title = {Diffusion Wavelet Packets}, author = {James Jr. C Bremer and Ronald R Coifman and Mauro Maggioni and Arthur D Szlam}, year = {2006}, date = {2006-07-01}, journal = {Appl. Comp. Harm. Anal.}, volume = {21}, number = {1}, pages = {95–112}, note = {(Tech. Rep. YALE/DCS/TR-1304, 2004)}, keywords = {diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

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 @inproceedings{CLMKSWZ:GeometrySensorOutputs, title = {Geometries of sensor outputs, inference, and information processing}, author = {Ronald R Coifman and Stephane Lafon and Mauro Maggioni and Y Keller and A D Szlam and F J Warner and S W Zucker}, editor = {John Zolper; Eds. C Intelligent Integrated Microsystems; Ravindra A. Athale}, year = {2006}, date = {2006-05-01}, booktitle = {Proc. SPIE}, volume = {6232}, pages = {623209}, keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {inproceedings} } |

Causevic, E; Coifman, Ronald R; Isenhart, R; Jacquin, A; John, E R; Maggioni, Mauro; Prichep, L S; Warner, F J QEEG-based classification with wavelet packets and microstate features for triage applications in the ER Inproceedings ICASSP Proc., 2006, (10.1109/ICASSP.2006.1660859). BibTeX | Tags: Clustering, hidden Markov models, Machine learning @inproceedings{MM:EEG, title = {QEEG-based classification with wavelet packets and microstate features for triage applications in the ER}, author = {E Causevic and Ronald R Coifman and R Isenhart and A Jacquin and E R John and Mauro Maggioni and L S Prichep and F J Warner}, year = {2006}, date = {2006-05-01}, volume = {3}, publisher = {ICASSP Proc.}, note = {10.1109/ICASSP.2006.1660859}, keywords = {Clustering, hidden Markov models, Machine learning}, pubstate = {published}, tppubtype = {inproceedings} } |

Coifman, Ronald R; Maggioni, Mauro Multiscale Analysis of Document Corpora Unpublished 2006, (Technical Report). BibTeX | Tags: Machine learning, Manifold Learning, multiscale analysis, Unsupervised Learning @unpublished{CM:MultiscaleAnalysisOfDocumentCorpora, title = {Multiscale Analysis of Document Corpora}, author = {Ronald R Coifman and Mauro Maggioni}, year = {2006}, date = {2006-01-01}, note = {Technical Report}, keywords = {Machine learning, Manifold Learning, multiscale analysis, Unsupervised Learning}, pubstate = {published}, tppubtype = {unpublished} } |

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 @inproceedings{smmm:FastDirectMDP, title = {Fast Direct Policy Evaluation using Multiscale Analysis of Markov Diffusion Processes}, author = {Mauro Maggioni and Sridhar Mahadevan}, year = {2006}, date = {2006-01-01}, booktitle = {ICML 2006}, pages = {601–608}, keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory}, pubstate = {published}, tppubtype = {inproceedings} } |

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 @inproceedings{smkfsomm:SimLearningReprControlContinuous, title = {Simultaneous Learning of Representation and Control In Continuous Domains}, author = {Sridhar Mahadevan and Kim Ferguson and Sarah Osentoski and Mauro Maggioni}, year = {2006}, date = {2006-01-01}, booktitle = {AAAI}, publisher = {AAAI Press}, keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory}, pubstate = {published}, tppubtype = {inproceedings} } |

Maggioni, Mauro; Davis, Gus L; Warner, F J; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A; Coifman, Ronald R Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections Conference 6091 (1), SPIE, San Jose, CA, USA, 2006. BibTeX | Tags: Clustering, hyperspectral imaging, imaging, Machine learning, supervised learning @conference{maggioni:60910I, title = {Hyperspectral microscopic analysis of normal, benign and carcinoma microarray tissue sections}, author = {Mauro Maggioni and Gus L Davis and F J Warner and Frank B Geshwind and Andreas C Coppi and R A DeVerse and Ronald R Coifman}, editor = {Robert R Alfano and Alvin Katz}, year = {2006}, date = {2006-01-01}, journal = {Optical Biopsy VI}, volume = {6091}, number = {1}, pages = {60910I}, publisher = {SPIE}, address = {San Jose, CA, USA}, keywords = {Clustering, hyperspectral imaging, imaging, Machine learning, supervised learning}, pubstate = {published}, tppubtype = {conference} } |

Mahoney, Michael W; Maggioni, Mauro; Drineas, Petros Tensor-CUR Decompositions For Tensor-Based Data Inproceedings Proc 12-th Annual SIGKDD, 2006. BibTeX | Tags: computational mathematics @inproceedings{MMD:TensorCUR, title = {Tensor-CUR Decompositions For Tensor-Based Data}, author = {Michael W Mahoney and Mauro Maggioni and Petros Drineas}, year = {2006}, date = {2006-01-01}, booktitle = {Proc 12-th Annual SIGKDD}, keywords = {computational mathematics}, pubstate = {published}, tppubtype = {inproceedings} } |

## 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 @article{CMZK:CONB, title = {Geometric diffusions for the analysis of data from sensor networks}, author = {Ronald R Coifman and Mauro Maggioni and Steven W Zucker and Ioannis G Kevrekidis}, year = {2005}, date = {2005-10-01}, journal = {Curr Opin Neurobiol}, volume = {15}, number = {5}, pages = {576–84}, keywords = {diffusion geometry, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

Coifman, Ronald R; Lafon, Stephane; Lee, Ann B; Maggioni, Mauro; Nadler, B; Warner, Frederick; Zucker, Steven W Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps Journal Article Proceedings of the National Academy of Sciences of the United States of America, 102 (21), pp. 7426-7431, 2005. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems @article{DiffusionPNAS, title = {Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps}, author = {Ronald R Coifman and Stephane Lafon and Ann B Lee and Mauro Maggioni and B Nadler and Frederick Warner and Steven W Zucker}, year = {2005}, date = {2005-01-01}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {102}, number = {21}, pages = {7426-7431}, keywords = {diffusion geometry, Machine learning, Manifold Learning, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

Coifman, Ronald R; Lafon, S; Lee, A B; Maggioni, Mauro; Nadler, B; Warner, Frederick; Zucker, Steven W Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods Journal Article Proceedings of the National Academy of Sciences of the United States of America, 102 (21), pp. 7432–7438, 2005. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems @article{DiffusionPNAS2, title = {Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods}, author = {Ronald R Coifman and S Lafon and A B Lee and Mauro Maggioni and B Nadler and Frederick Warner and Steven W Zucker}, year = {2005}, date = {2005-01-01}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {102}, number = {21}, pages = {7432–7438}, keywords = {diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {article} } |

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 @inproceedings{smmm:ValueFunction, title = {Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions}, author = {Sridhar Mahadevan and Mauro Maggioni}, year = {2005}, date = {2005-01-01}, booktitle = {University of Massachusetts, Department of Computer Science Technical Report TR-2005-38; Proc. NIPS 2005}, keywords = {diffusion geometry, diffusion wavelets, Laplacian eigenfunctions, Machine learning, Manifold Learning, random walks, reinforcement learning, representation learning, spectral graph theory}, pubstate = {published}, tppubtype = {inproceedings} } |

Maggioni, Mauro; Bremer, James Jr. C; Coifman, Ronald R; Szlam, Arthur D Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs Conference 5914 (1), SPIE, San Diego, CA, USA, 2005. Links | BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory @conference{MBCS:BiorthogonalDiffusionWavelets, title = {Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs}, author = {Mauro Maggioni and James Jr. C Bremer and Ronald R Coifman and Arthur D Szlam}, editor = {Manos Papadakis and Andrew F Laine and Michael A Unser}, url = {http://link.aip.org/link/?PSI/5914/59141M/1}, year = {2005}, date = {2005-01-01}, journal = {Wavelets XI}, volume = {5914}, number = {1}, pages = {59141M}, publisher = {SPIE}, address = {San Diego, CA, USA}, keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory}, pubstate = {published}, tppubtype = {conference} } |

Szlam, Arthur D; Maggioni, Mauro; Coifman, Ronald R; Bremer, James Jr. C Diffusion-driven multiscale analysis on manifolds and graphs: top-down and bottom-up constructions Conference 5914-1 , SPIE, San Diego, CA, USA, 2005. Links | BibTeX | Tags: diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory @conference{MSCB:MultiscaleManifoldMethods, title = {Diffusion-driven multiscale analysis on manifolds and graphs: top-down and bottom-up constructions}, author = {Arthur D Szlam and Mauro Maggioni and Ronald R Coifman and James Jr. C Bremer}, editor = {Manos Papadakis and Andrew F Laine and Michael A Unser}, url = {http://link.aip.org/link/?PSI/5914/59141D/1}, year = {2005}, date = {2005-01-01}, journal = {Wavelets XI}, volume = {5914-1}, pages = {59141D}, publisher = {SPIE}, address = {San Diego, CA, USA}, keywords = {diffusion geometry, diffusion wavelets, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory}, pubstate = {published}, tppubtype = {conference} } |

## 2004 |

Goetzmann, William; Jones, Peter W; Maggioni, Mauro; Walden, Johan Beauty is in the eye of the beholder Journal Article submitted, 2004. BibTeX | Tags: @article{GoetzmannBeauty, title = {Beauty is in the eye of the beholder}, author = {William Goetzmann and Peter W Jones and Mauro Maggioni and Johan Walden}, year = {2004}, date = {2004-09-01}, journal = {submitted}, keywords = {}, pubstate = {published}, tppubtype = {article} } |

Davis, Gus L; Maggioni, Mauro; Warner, F J; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A; Coifman, Ronald R Hyper-spectral Analysis of normal and malignant colon tissue microarray sections using a novel DMD system Miscellaneous Poster, Optical Imaging NIH workshop, to app. in proc., 2004. BibTeX | Tags: hyperspectral imaging, imaging, medical imaging @misc{PathNIH2004, title = {Hyper-spectral Analysis of normal and malignant colon tissue microarray sections using a novel DMD system}, author = {Gus L Davis and Mauro Maggioni and F J Warner and Frank B Geshwind and Andreas C Coppi and R A DeVerse and Ronald R Coifman}, year = {2004}, date = {2004-09-01}, howpublished = {Poster, Optical Imaging NIH workshop, to app. in proc.}, keywords = {hyperspectral imaging, imaging, medical imaging}, pubstate = {published}, tppubtype = {misc} } |

Coifman, Ronald R; Maggioni, Mauro Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms Technical Report Dept. Comp. Sci., Yale University (YALE/DCS/TR-1289), 2004. BibTeX | Tags: diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems @techreport{CMTech, title = {Multiresolution Analysis associated to diffusion semigroups: construction and fast algorithms}, author = {Ronald R Coifman and Mauro Maggioni}, year = {2004}, date = {2004-05-01}, number = {YALE/DCS/TR-1289}, institution = {Dept. Comp. Sci., Yale University}, keywords = {diffusion geometry, Machine learning, Manifold Learning, multiscale analysis, random walks, spectral graph theory, stochastic systems}, pubstate = {published}, tppubtype = {techreport} } |

Maggioni, Mauro; Warner, F J; Davis, Gus L; Coifman, Ronald R; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections Technical Report Yale University Dept. Comp. Sci., (1311), 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @techreport{MMPathTechRep, title = {Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections}, author = {Mauro Maggioni and F J Warner and Gus L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and R A DeVerse}, year = {2004}, date = {2004-02-01}, number = {1311}, address = {Dept. Comp. Sci.}, institution = {Yale University}, keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning}, pubstate = {published}, tppubtype = {techreport} } |

Ferrari, S; Maggioni, Mauro; Borghese, N A Multi-Scale Approximation with Hierarchical Radial Basis Functions Networks, Journal Article IEEE Trans. on Neural Networks, 15 (1), pp. 178–188, 2004. BibTeX | Tags: approximation theory, multiscale analysis, radial basis functions @article{MRA_HRBF2004, title = {Multi-Scale Approximation with Hierarchical Radial Basis Functions Networks,}, author = {S Ferrari and Mauro Maggioni and N A Borghese}, year = {2004}, date = {2004-01-01}, journal = {IEEE Trans. on Neural Networks}, volume = {15}, number = {1}, pages = {178–188}, keywords = {approximation theory, multiscale analysis, radial basis functions}, pubstate = {published}, tppubtype = {article} } |

Cassidy, Ryan J; Berger, Jim; Maggioni, Mauro; Coifman, Ronald R Auditory display of hyperspectral colon tissue images using vocal synthesis models Journal Article Proc. 2004 Intern. Con. Auditory Display, 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning @article{AuditoryDisplay, title = {Auditory display of hyperspectral colon tissue images using vocal synthesis models}, author = {Ryan J Cassidy and Jim Berger and Mauro Maggioni and Ronald R Coifman}, year = {2004}, date = {2004-01-01}, journal = {Proc. 2004 Intern. Con. Auditory Display}, keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning}, pubstate = {published}, tppubtype = {article} } |

Davis, Gus L; Maggioni, Mauro; Coifman, Ronald R; Levinson, R; Rimm, D Spatial-Spectral Analysis of Colon Carcinoma Journal Article Mod. Path., 2004, (In print). BibTeX | Tags: hyperspectral imaging, imaging, medical imaging @article{ModPath:2003, title = {Spatial-Spectral Analysis of Colon Carcinoma}, author = {Gus L Davis and Mauro Maggioni and Ronald R Coifman and R Levinson and D Rimm}, year = {2004}, date = {2004-01-01}, journal = {Mod. Path.}, note = {In print}, keywords = {hyperspectral imaging, imaging, medical imaging}, pubstate = {published}, tppubtype = {article} } |

Davis, Gus L; Maggioni, Mauro; Warner, F J; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A; Coifman, Ronald R Spectral Analysis of normal and Malignant Microarray Tissue Sections using a novel micro-optoelectrialmechanical system Journal Article Mod Pathol, 17 (1:358A), 2004. BibTeX | Tags: hyperspectral imaging, imaging, medical imaging @article{ModPath:2004, title = {Spectral Analysis of normal and Malignant Microarray Tissue Sections using a novel micro-optoelectrialmechanical system}, author = {Gus L Davis and Mauro Maggioni and F J Warner and Frank B Geshwind and Andreas C Coppi and R A DeVerse and Ronald R Coifman}, year = {2004}, date = {2004-01-01}, journal = {Mod Pathol}, volume = {17}, number = {1:358A}, keywords = {hyperspectral imaging, imaging, medical imaging}, pubstate = {published}, tppubtype = {article} } |

Maggioni, Mauro; Warner, F J; Davis, Gus L; Coifman, Ronald R; Geshwind, Frank B; Coppi, Andreas C; DeVerse, R A Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections Journal Article submitted, 2004. BibTeX | Tags: Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning @article{MMIEEEPath, title = {Algorithms from Signal and Data Processing Applied to Hyperspectral Analysis: Application to Discriminating Normal and Malignant Microarray Colon Tissue Sections}, author = {Mauro Maggioni and F J Warner and Gus L Davis and Ronald R Coifman and Frank B Geshwind and Andreas C Coppi and R A DeVerse}, year = {2004}, date = {2004-01-01}, journal = {submitted}, keywords = {Clustering, diffusion geometry, hyperspectral images, Machine learning, Unsupervised Learning}, pubstate = {published}, tppubtype = {article} } |

Maggioni, Mauro Wavelet frames on groups and hypergroups via discretization of Calderón formulas Journal Article Monats. Mat., (143), pp. 299–331, 2004. BibTeX | Tags: harmonic analysis, wavelets @article{MM_WaveletFrames, title = {Wavelet frames on groups and hypergroups via discretization of Calderón formulas}, author = {Mauro Maggioni}, year = {2004}, date = {2004-01-01}, journal = {Monats. Mat.}, number = {143}, pages = {299–331}, keywords = {harmonic analysis, wavelets}, pubstate = {published}, tppubtype = {article} } |

## 2002 |

Chui, Charles K; Czaja, Wojciech; Maggioni, Mauro; Weiss, Guido Characterization of Tight Wavelet Frames with Arbitrary Matrix Dilations and Tightness Preserving Oversampling Journal Article J Four Anal App, 8 (2), pp. 173-200, 2002. BibTeX | Tags: harmonic analysis, wavelets @article{CCMW, title = {Characterization of Tight Wavelet Frames with Arbitrary Matrix Dilations and Tightness Preserving Oversampling}, author = {Charles K Chui and Wojciech Czaja and Mauro Maggioni and Guido Weiss}, year = {2002}, date = {2002-01-01}, journal = {J Four Anal App}, volume = {8}, number = {2}, pages = {173-200}, keywords = {harmonic analysis, wavelets}, pubstate = {published}, tppubtype = {article} } |

Katz, Nets H; Krop, Elliot; Maggioni, Mauro Remarks on the box problem Journal Article Math. Research Letters, 4 , pp. 515-519, 2002. Links | BibTeX | Tags: combinatorics, harmonic analysis @article{Box, title = {Remarks on the box problem}, author = {Nets H Katz and Elliot Krop and Mauro Maggioni}, url = {https://core.ac.uk/display/20985482}, year = {2002}, date = {2002-01-01}, journal = {Math. Research Letters}, volume = {4}, pages = {515-519}, keywords = {combinatorics, harmonic analysis}, pubstate = {published}, tppubtype = {article} } |

## 2000 |

Maggioni, Mauro M-Band Burt-Adelson Wavelets Journal Article Appl. Comput. Harm. Anal., 3 , pp. 286-311, 2000. BibTeX | Tags: harmonic analysis, wavelets @article{MBand, title = {M-Band Burt-Adelson Wavelets}, author = {Mauro Maggioni}, year = {2000}, date = {2000-01-01}, journal = {Appl. Comput. Harm. Anal.}, volume = {3}, pages = {286-311}, keywords = {harmonic analysis, wavelets}, pubstate = {published}, tppubtype = {article} } |

Maggioni, Mauro Critical Exponent of Short Even Filters and Biorthogonal Burt-Adelson Wavelets Journal Article Monats. Math., 131 (1), pp. 49-70, 2000. BibTeX | Tags: harmonic analysis, wavelets @article{CriticalExponent, title = {Critical Exponent of Short Even Filters and Biorthogonal Burt-Adelson Wavelets}, author = {Mauro Maggioni}, year = {2000}, date = {2000-01-01}, journal = {Monats. Math.}, volume = {131}, number = {1}, pages = {49-70}, keywords = {harmonic analysis, wavelets}, pubstate = {published}, tppubtype = {article} } |

## 0000 |

Lu, Fei; Maggioni, Mauro; Tang, Sui Learning interaction kernels in heterogeneous systems of agents from multiple trajectories Journal Article Journ. Mach. Learn. Res., 22 (32), pp. 1–67, 0000. Links | BibTeX | Tags: agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics @article{LMT:AgentsHeterogeneous, title = {Learning interaction kernels in heterogeneous systems of agents from multiple trajectories}, author = {Fei Lu and Mauro Maggioni and Sui Tang}, url = {https://jmlr.csail.mit.edu/papers/volume22/19-861/19-861.pdf}, journal = {Journ. Mach. Learn. Res.}, volume = {22}, number = {32}, pages = {1–67}, keywords = {agent-based models, interacting particle systems, inverse problems, Machine learning, model reduction, statistics}, pubstate = {published}, tppubtype = {article} } |

- Lectures at Summer School at Peking University, July 2017.
- PCMI Lectures, Summer 2016: Lecture 1, Lecture 2, Problems/discussion points
- Google Scholar
- Papers on the ArXiv
- Papers on MathsciNet
- Tutorials on diffusion geometry and multiscale analysis on graphs at the MRA Internet Program at IPAM: Part I and Part II.
- Diffusion Geometries, Diffusion Wavelets and Harmonic Analysis of large data sets, IPAM, Multiscale Geometric Analysis Program, Fall 2004.
- Diffusion Geometries, global and multiscale, IPAM, 2005.