
Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides
Building accurate and predictive models of the underlying mechanisms of ...
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Nonlinear model reduction for slowfast stochastic systems near manifolds
We introduce a nonlinear stochastic model reduction technique for highd...
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Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Interacting agent and particle systems are extensively used to model com...
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Multiscale regression on unknown manifolds
We consider the regression problem of estimating functions on ℝ^D but su...
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AnatomicallyInformed Deep Learning on ContrastEnhanced Cardiac MRI for Scar Segmentation and Clinical Feature Extraction
Many cardiac diseases are associated with structural remodeling of the m...
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Learning Theory for Inferring Interaction Kernels in SecondOrder Interacting Agent Systems
Modeling the complex interactions of systems of particles or agents is a...
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Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories
We consider stochastic systems of interacting particles or agents, with ...
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Conditional regression for singleindex models
The singleindex model is a statistical model for intrinsic regression w...
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On the identifiability of interaction functions in systems of interacting particles
Identifiability is of fundamental importance in the statistical learning...
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Datadriven Discovery of Emergent Behaviors in Collective Dynamics
Particle and agentbased systems are a ubiquitous modeling tool in many...
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Learning interaction kernels in heterogeneous systems of agents from multiple trajectories
Systems of interacting particles or agents have wide applications in man...
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Learning by Active Nonlinear Diffusion
This article proposes an active learning method for high dimensional dat...
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SpectralSpatial Diffusion Geometry for Hyperspectral Image Clustering
An unsupervised learning algorithm to cluster hyperspectral image (HSI) ...
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Nonparametric inference of interaction laws in systems of agents from trajectory data
Inferring the laws of interaction between particles and agents in comple...
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Learning by Unsupervised Nonlinear Diffusion
This paper proposes and analyzes a novel clustering algorithm that combi...
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PathBased Spectral Clustering: Guarantees, Robustness to Outliers, and Fast Algorithms
We consider the problem of clustering with the longest leg path distance...
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Linear Optimal Low Rank Projection for HighDimensional MultiClass Data
Classification of individual samples into one or more categories is crit...
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Adaptive Geometric Multiscale Approximations for Intrinsically Lowdimensional Data
We consider the problem of efficiently approximating and encoding highd...
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Discovering Relationships and their Structures Across Disparate Data Modalities
Determining whether certain properties are related to other properties i...
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High Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies
We briefly review recent progress in techniques for modeling and analyzi...
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Randomer Forests
Random forests (RF) is a popular general purpose classifier that has bee...
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Multiscale Markov Decision Problems: Compression, Solution, and Transfer Learning
Many problems in sequential decision making and stochastic control often...
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Multiscale Geometric Methods for Data Sets II: Geometric MultiResolution Analysis
Data sets are often modeled as point clouds in R^D, for D large. It is o...
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Mauro Maggioni
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