Mauro Maggioni
Orcid: 0000-0003-3258-9297
According to our database1,
Mauro Maggioni
authored at least 64 papers
between 2004 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
A scalable framework for learning the geometry-dependent solution operators of partial differential equations.
Nat. Comput. Sci., December, 2024
IEEE Trans. Inf. Theory, September, 2024
Nonlinear Model Reduction for Slow-Fast Stochastic Systems Near Unknown Invariant Manifolds.
J. Nonlinear Sci., February, 2024
Diffeomorphic Latent Neural Operators for Data-Efficient Learning of Solutions to Partial Differential Equations.
CoRR, 2024
Graph Fourier Neural Kernels (G-FuNK): Learning Solutions of Nonlinear Diffusive Parametric PDEs on Multiple Domains.
CoRR, 2024
Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints.
CoRR, 2024
Interacting Particle Systems on Networks: joint inference of the network and the interaction kernel.
CoRR, 2024
DIMON: Learning Solution Operators of Partial Differential Equations on a Diffeomorphic Family of Domains.
CoRR, 2024
2022
Learning Interaction Kernels in Stochastic Systems of Interacting Particles from Multiple Trajectories.
Found. Comput. Math., 2022
CoRR, 2022
Unsupervised learning of observation functions in state-space models by nonparametric moment methods.
CoRR, 2022
2021
Learning interaction kernels in heterogeneous systems of agents from multiple trajectories.
J. Mach. Learn. Res., 2021
Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides.
CoRR, 2021
CoRR, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
IEEE Geosci. Remote. Sens. Lett., 2020
Path-Based Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms.
J. Mach. Learn. Res., 2020
Anatomically-Informed Deep Learning on Contrast-Enhanced Cardiac MRI for Scar Segmentation and Clinical Feature Extraction.
CoRR, 2020
Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems.
CoRR, 2020
2019
Unsupervised Clustering and Active Learning of Hyperspectral Images With Nonlinear Diffusion.
IEEE Trans. Geosci. Remote. Sens., 2019
J. Mach. Learn. Res., 2019
Unsupervised Discriminative Dimension Reduction for Hyperspectral Chemical Plume Segmentation.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
Nonparametric inference of interaction laws in systems of agents from trajectory data.
CoRR, 2018
Proceedings of the 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2018
2017
ATLAS: A Geometric Approach to Learning High-Dimensional Stochastic Systems Near Manifolds.
Multiscale Model. Simul., 2017
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017
2016
High-Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016
J. Mach. Learn. Res., 2016
Learning adaptive multiscale approximations to data and functions near low-dimensional sets.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
2015
Enhanced detection of chemical plumes in hyperspectral images and movies throughimproved backgroundmodeling.
Proceedings of the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2015
2014
PLoS Comput. Biol., 2014
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14).
CoRR, 2014
2013
Proceedings of the 2013 Asilomar Conference on Signals, 2013
2012
CoRR, 2012
CoRR, 2012
A fast multiscale framework for data in high-dimensions: Measure estimation, anomaly detection, and compressive measurements.
Proceedings of the 2012 Visual Communications and Image Processing, 2012
Proceedings of the 51th IEEE Conference on Decision and Control, 2012
Proceedings of the 50th Annual Allerton Conference on Communication, 2012
2011
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011
2010
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence.
J. Mach. Learn. Res., 2010
Proceedings of the 5th IEEE Conference on Visual Analytics Science and Technology, 2010
Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010
2009
SIGMETRICS Perform. Evaluation Rev., 2009
Proceedings of the Manifold Learning and Its Applications, 2009
2008
Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems.
Multiscale Model. Simul., 2008
J. Mach. Learn. Res., 2008
2007
Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes.
J. Mach. Learn. Res., 2007
2006
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes.
Proceedings of the Machine Learning, 2006
Qeeg-Based Classification With Wavelet Packet and Microstate Features for Triage Applications in the ER.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006
Proceedings of the Proceedings, 2006
2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
2004
IEEE Trans. Neural Networks, 2004