Multiscale approximation with hierarchical radial basis functions networks. - Stefano Ferrari; Mauro Maggioni; N. Alberto Borghese (IEEE Trans. Neural Networks, 2004)

Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions. - Sridhar Mahadevan; Mauro Maggioni (NIPS, 2005)

Learning Representation and Control in Continuous Markov Decision Processes. - Sridhar Mahadevan; Mauro Maggioni; Kimberly Ferguson; Sarah Osentoski (AAAI, 2006)

Qeeg-Based Classification With Wavelet Packet and Microstate Features for Triage Applications in the ER. - Leslie S. Prichep; Elvir Causevic; Ronald R. Coifman; Robert Isenhart; Arnaud E. Jacquin; E. Roy John; Mauro Maggioni; Fred Warner (ICASSP (3), 2006)

Fast direct policy evaluation using multiscale analysis of Markov diffusion processes. - Mauro Maggioni; Sridhar Mahadevan (ICML, 2006)

Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes. - Sridhar Mahadevan; Mauro Maggioni (J. Mach. Learn. Res., 2007)

Regularization on Graphs with Function-adapted Diffusion Processes. - Arthur D. Szlam; Mauro Maggioni; Ronald R. Coifman (J. Mach. Learn. Res., 2008)

Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems. - Ronald R. Coifman; Ioannis G. Kevrekidis; Stéphane Lafon; Mauro Maggioni; Boaz Nadler (Multiscale Model. Simul., 2008)

Tensor-CUR Decompositions for Tensor-Based Data. - Michael W. Mahoney; Mauro Maggioni; Petros Drineas (SIAM J. Matrix Anal. Appl., 2008)

Multiscale Estimation of Intrinsic Dimensionality of Data Sets. - Anna V. Little; Yoon-Mo Jung; Mauro Maggioni (AAAI Fall Symposium: Manifold Learning and Its Applications, 2009)

Research on online social networks: time to face the real challenges. - Walter Willinger; Reza Rejaie; Mojtaba Torkjazi; Masoud Valafar; Mauro Maggioni (SIGMETRICS Perform. Evaluation Rev., 2009)

Multiscale geometric wavelets for the analysis of point clouds. - Guangliang Chen; Mauro Maggioni (CISS, 2010)

Data representation and exploration with Geometric Wavelets. - Eric E. Monson; Guangliang Chen; Rachel Brady; Mauro Maggioni (IEEE VAST, 2010)

Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence. - Qiang Wu 003; Justin Guinney; Mauro Maggioni; Sayan Mukherjee 001 (J. Mach. Learn. Res., 2010)

Multiscale geometric and spectral analysis of plane arrangements. - Guangliang Chen; Mauro Maggioni (CVPR, 2011)

Multiscale Geometric Methods for Data Sets II: Geometric Wavelets - William K. Allard; Guangliang Chen; Mauro Maggioni (CoRR, 2011)

Efficient solution of Markov decision problems with multiscale representations. - Jake V. Bouvrie; Mauro Maggioni (Allerton Conference, 2012)

Geometric multiscale reduction for autonomous and controlled nonlinear systems. - Jake V. Bouvrie; Mauro Maggioni (CDC, 2012)

A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements. - Guangliang Chen; Mark A. Iwen; Sang Chin 001; Mauro Maggioni (VCIP, 2012)

Approximation of Points on Low-Dimensional Manifolds Via Random Linear Projections - Mark A. Iwen; Mauro Maggioni (CoRR, 2012)

Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning - Jake V. Bouvrie; Mauro Maggioni (CoRR, 2012)

Geometric estimation of probability measures in high-dimensions. - Mauro Maggioni (ACSSC, 2013)

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). - Laurent Jacques; Christophe De Vleeschouwer; Yannick Boursier; Prasad Sudhakar; C. De Mol; Aleksandra Pizurica; Sandrine Anthoine; Pierre Vandergheynst; Pascal Frossard; Cagdas Bilen; Srdan Kitic; Nancy Bertin; et al. (CoRR, 2014)

Genomic Characterization of Large Heterochromatic Gaps in the Human Genome Assembly. - Nicolas Altemose; Karen H. Miga; Mauro Maggioni; Huntington F. Willard (PLoS Comput. Biol., 2014)

Enhanced detection of chemical plumes in hyperspectral images and movies throughimproved backgroundmodeling. - Yi Grace Wang; Mauro Maggioni; Guangliang Chen (WHISPERS, 2015)

Randomer Forests. - Tyler M. Tomita; Mauro Maggioni; Joshua T. Vogelstein (CoRR, 2015)

Object recognition in art drawings: Transfer of a neural network. - Rujie Yin; Eric E. Monson; Elizabeth Honig; Ingrid Daubechies; Mauro Maggioni (ICASSP, 2016)

Learning adaptive multiscale approximations to data and functions near low-dimensional sets. - Wenjing Liao; Mauro Maggioni; Stefano Vigogna (ITW, 2016)

Multiscale Dictionary Learning: Non-Asymptotic Bounds and Robustness. - Mauro Maggioni; Stanislav Minsker; Nate Strawn (J. Mach. Learn. Res., 2016)

High-Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies. - Yi Wang 009; Guangliang Chen; Mauro Maggioni (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016)

ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations. - Tyler M. Tomita; Mauro Maggioni; Joshua T. Vogelstein (SDM, 2017)

Unsupervised Geometric Learning of Hyperspectral Images. - James M. Murphy; Mauro Maggioni (CoRR, 2017)

Multiscale Strategies for Computing Optimal Transport. - Samuel Gerber; Mauro Maggioni (J. Mach. Learn. Res., 2017)

ATLAS: A Geometric Approach to Learning High-Dimensional Stochastic Systems Near Manifolds. - Miles Crosskey; Mauro Maggioni (Multiscale Model. Simul., 2017)

Iterative active learning with diffusion geometry for hyperspectral images. - James M. Murphy; Mauro Maggioni (WHISPERS, 2018)

Nonparametric inference of interaction laws in systems of agents from trajectory data. - Fei Lu 016; Mauro Maggioni; Sui Tang; Ming Zhong 008 (CoRR, 2018)

Unsupervised Discriminative Dimension Reduction for Hyperspectral Chemical Plume Segmentation. - James M. Murphy; Mauro Maggioni (IGARSS, 2019)

Learning by Active Nonlinear Diffusion. - Mauro Maggioni; James M. Murphy (CoRR, 2019)

Data-driven Discovery of Emergent Behaviors in Collective Dynamics. - Mauro Maggioni; Jason Miller; Ming Zhong 008 (CoRR, 2019)

Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data. - Wenjing Liao; Mauro Maggioni (J. Mach. Learn. Res., 2019)

Learning by Unsupervised Nonlinear Diffusion. - Mauro Maggioni; James M. Murphy (J. Mach. Learn. Res., 2019)

Unsupervised Clustering and Active Learning of Hyperspectral Images With Nonlinear Diffusion. - James M. Murphy; Mauro Maggioni (IEEE Trans. Geosci. Remote. Sens., 2019)

Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems. - Jason Miller; Sui Tang; Ming Zhong 008; Mauro Maggioni (CoRR, 2020)

Anatomically-Informed Deep Learning on Contrast-Enhanced Cardiac MRI for Scar Segmentation and Clinical Feature Extraction. - Haley G. Abramson; Dan M. Popescu; Rebecca Yu; Changxin Lai; Julie K. Shade; Katherine C. Wu; Mauro Maggioni; Natalia A. Trayanova (CoRR, 2020)

Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms. - Anna V. Little; Mauro Maggioni; James M. Murphy (J. Mach. Learn. Res., 2020)

Sparse Projection Oblique Randomer Forests. - Tyler M. Tomita; James Browne; Cencheng Shen; Jaewon Chung; Jesse Patsolic; Benjamin Falk; Carey E. Priebe; Jason Yim; Randal C. Burns; Mauro Maggioni; Joshua T. Vogelstein (J. Mach. Learn. Res., 2020)

Spectral-Spatial Diffusion Geometry for Hyperspectral Image Clustering. - James M. Murphy; Mauro Maggioni (IEEE Geosci. Remote. Sens. Lett., 2020)

Learning Interaction Kernels for Agent Systems on Riemannian Manifolds. - Mauro Maggioni; Jason Miller; Hongda Qiu; Ming Zhong 008 (ICML, 2021)

Multiscale regression on unknown manifolds. - Wenjing Liao; Mauro Maggioni; Stefano Vigogna (CoRR, 2021)

Nonlinear model reduction for slow-fast stochastic systems near manifolds. - Felix X.-F. Ye; Sichen Yang; Mauro Maggioni (CoRR, 2021)

Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides. - Ming Zhong 008; Jason Miller; Mauro Maggioni (CoRR, 2021)

Learning interaction kernels in heterogeneous systems of agents from multiple trajectories. - Fei Lu 016; Mauro Maggioni; Sui Tang (J. Mach. Learn. Res., 2021)

Unsupervised learning of observation functions in state-space models by nonparametric moment methods. - Qingci An; Yannis G. Kevrekidis; Fei Lu 016; Mauro Maggioni (CoRR, 2022)

Learning Interaction Variables and Kernels from Observations of Agent-Based Systems. - Jinchao Feng; Mauro Maggioni; Patrick Martin; Ming Zhong 008 (CoRR, 2022)

Learning Interaction Kernels in Stochastic Systems of Interacting Particles from Multiple Trajectories. - Fei Lu 016; Mauro Maggioni; Sui Tang (Found. Comput. Math., 2022)

DIMON: Learning Solution Operators of Partial Differential Equations on a Diffeomorphic Family of Domains. - Minglang Yin; Nicolas Charon; Ryan Brody; Lu Lu 010; Natalia A. Trayanova; Mauro Maggioni (CoRR, 2024)

Interacting Particle Systems on Networks: joint inference of the network and the interaction kernel. - Quanjun Lang; Xiong Wang; Fei Lu 016; Mauro Maggioni (CoRR, 2024)

Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints. - George A. Kevrekidis; Mauro Maggioni; Soledad Villar; Yannis G. Kevrekidis (CoRR, 2024)

Graph Fourier Neural Kernels (G-FuNK): Learning Solutions of Nonlinear Diffusive Parametric PDEs on Multiple Domains. - Shane E. Loeffler; Zan Ahmad; Syed Yusuf Ali; Carolyna A. P. Yamamoto; Dan M. Popescu; Alana Yee; Yash Lal; Natalia A. Trayanova; Mauro Maggioni (CoRR, 2024)

Conditional regression for the Nonlinear Single-Variable Model. - Yantao Wu; Mauro Maggioni (CoRR, 2024)

Diffeomorphic Latent Neural Operators for Data-Efficient Learning of Solutions to Partial Differential Equations. - Zan Ahmad; Shiyi Chen; Minglang Yin; Avisha Kumar; Nicolas Charon; Natalia A. Trayanova; Mauro Maggioni (CoRR, 2024)

Nonlinear Model Reduction for Slow-Fast Stochastic Systems Near Unknown Invariant Manifolds. - Felix X.-F. Ye; Sichen Yang; Mauro Maggioni (J. Nonlinear Sci., 2024)

Learning Transition Operators From Sparse Space-Time Samples. - Christian Kümmerle; Mauro Maggioni; Sui Tang (IEEE Trans. Inf. Theory, 2024)

A scalable framework for learning the geometry-dependent solution operators of partial differential equations. - Minglang Yin; Nicolas Charon; Ryan Brody; Lu Lu 010; Natalia A. Trayanova; Mauro Maggioni (Nat. Comput. Sci., 2024)