Kinetic Euclidean Distance Matrices

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The accurate, robust and efficient transfer of the deformation gradient tensor between meshes of different resolution is crucial in cardiac electromechanics simulations. This paper presents a novel method that combines rescaled localized Radial Basis Funct ...

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In this manuscript we consider denoising of large rectangular matrices: given a noisy observation of a signal matrix, what is the best way of recovering the signal matrix itself? For Gaussian noise and rotationally-invariant signal priors, we completely ch ...

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The Schur decomposition of a square matrix A is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following task: Compute a (m ...

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We consider increasingly complex models of matrix denoising and dictionary learning in the Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank growing linearly with the system size. This is in contrast with most existin ...

This work is concerned with approximating matrix functions for banded matrices, hierarchically semiseparable matrices, and related structures. We develop a new divide-and-conquer method based on (rational) Krylov subspace methods for performing low-rank up ...

Kinetic Euclidean Distance Matrices

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Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: Application to cardiac electromechanics

Indoor Real-time localization system design for Internet of Things applications

De novo protein design by inversion of the AlphaFold structure prediction network

A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

Hands-on reservoir computing: a tutorial for practical implementation

Optimal denoising of rotationally invariant rectangular matrices

The double exponential runtime is tight for 2-stage stochastic ILPs

Iterative refinement of Schur decompositions

Deep learning approaches for conformational flexibility and switching properties in protein design

Scaffolding protein functional sites using deep learning

GNSS/INS Kalman Filter Integrity Monitoring with Uncertain Time Correlated Error Processes

Harmonic decomposition of the trace of 1D transfer matrices in layered media

A Capacitively-Coupled Chopper Instrumentation Amplifier for Implantable Bridge Sensor Systems

Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

DIVIDE-AND-CONQUER METHODS FOR FUNCTIONS OF MATRICES WITH BANDED OR HIERARCHICAL LOW-RANK STRUCTURE\ast