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Found 6 papers, 1 papers with code
Distance preservation in state-space methods for detecting causal interactions in dynamical systems
We analyze the popular ``state-space'' class of algorithms for detecting casual interaction in coupled dynamical systems.
Iterative Broadband Source Localization
We show that by using these models, our adapted algorithms can successfully localize broadband sources under a variety of adverse operating scenarios.
Broadband Beamforming via Linear Embedding
In modern applications multi-sensor arrays are subject to an ever-present demand to accommodate signals with higher bandwidths.
Generative causal explanations of black-box classifiers
Our objective function encourages both the generative model to faithfully represent the data distribution and the latent factors to have a large causal influence on the classifier output.
Sample complexity and effective dimension for regression on manifolds
We consider the theory of regression on a manifold using reproducing kernel Hilbert space methods.
A unified framework for manifold landmarking
Active manifold learning aims to select and label representative landmarks on a manifold from a given set of samples to improve semi-supervised manifold learning.
