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Found 6 papers, 4 papers with code
Tensor Moments of Gaussian Mixture Models: Theory and Applications
In this work, we develop theory and numerical methods for \emph{implicit computations} with moment tensors of GMMs, reducing the computational and storage costs to $\mathcal{O}(n^2)$ and $\mathcal{O}(n^3)$, respectively, for general covariance matrices, and to $\mathcal{O}(n)$ and $\mathcal{O}(n)$, respectively, for diagonal ones.
Landscape analysis of an improved power method for tensor decomposition
In this work, we consider the optimization formulation for symmetric tensor decomposition recently introduced in the Subspace Power Method (SPM) of Kileel and Pereira.
Identifying Latent Stochastic Differential Equations
We present a method for learning latent stochastic differential equations (SDEs) from high-dimensional time series data.
Robust Marine Buoy Placement for Ship Detection Using Dropout K-Means
Marine buoys aid in the battle against Illegal, Unreported and Unregulated (IUU) fishing by detecting fishing vessels in their vicinity.
Subspace power method for symmetric tensor decomposition and generalized PCA
We introduce the Subspace Power Method (SPM) for calculating the CP decomposition of low-rank even-order real symmetric tensors.
Numerical Analysis Numerical Analysis Optimization and Control
Learning Partial Differential Equations from Data Using Neural Networks
We develop a framework for estimating unknown partial differential equations from noisy data, using a deep learning approach.
