Certified And Fast Computations With Shallow Covariance Kernels

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Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

In this thesis we will present and analyze randomized algorithms for numerical linear algebra problems. An important theme in this thesis is randomized low-rank approximation. In particular, we will study randomized low-rank approximation of matrix functio ...

Plant cells harness osmotic pressures to stiffen their leaves through strong turgor pressures. Key to this osmosisdriven stiffening is the confinement of liquids within semipermeable membranes that can regulate the transport of water molecules and ions. In ...

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

Wastewater-based epidemiology offers a complementary approach to clinical case-based surveillance of emergent diseases and can help identify regions with infected people to prioritize clinical surveillance strategies. However, tracking emergent diseases in ...

We introduce and derive the Fourier -enhanced 3D electrostatic field solver of the gyrokinetic full -f PIC code PICLS. The solver makes use of a Fourier representation in one periodic direction of the domain to make the solving of the system easily paralle ...

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

Randomized measurement protocols such as classical shadows represent powerful resources for quantum technologies, with applications ranging from quantum state characterization and process tomography to machine learning and error mitigation. Recently, the n ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

This thesis concerns the theory of positive-definite completions and its mutually beneficial connections to the statistics of function-valued or continuously-indexed random processes, better known as functional data analysis. In particular, it dwells upon ...

Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projecti ...

Injection molding is known to create a layered anisotropicmorphologyacross the sample thickness due to varying shear and cooling ratesduring the manufacturing process. In this study, scanning small-angleX-ray scattering was used to visualize and quantify t ...

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

Head tracking combined with head movements have been shown to improve auditory externalization of a virtual sound source and contribute to the performance in localization. With certain technically constrained head-tracking algorithms, as can be found in we ...

ObjectiveWall shear stress (WSS) and its derived spatiotemporal parameters have proven to play a major role on intracranial aneurysms (IAs) growth and rupture. This study aims to demonstrate how ultra-high field (UHF) 7 T phase contrast magnetic resonance ...

Certified And Fast Computations With Shallow Covariance Kernels

Chattez avec Graph Search

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Spectral Estimators for High-Dimensional Matrix Inference

Transportation-based functional ANOVA and PCA for covariance operators

Random matrix methods for high-dimensional machine learning models

Randomized low-rank approximation and its applications

Osmosis-driven stiffening of structured hydrogels

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Monitoring an Emergent Pathogen at Low Incidence in Wastewater Using qPCR: Mpox in Switzerland

Verification of the Fourier-enhanced 3D finite element Poisson solver of the gyrokinetic full-f code PICLS

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Dual-frame optimization for informationally complete quantum measurements

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Positive Definite Completions and Continuous Graphical Models

Tangent functional connectomes uncover more unique phenotypic traits

Scanning Small-Angle X-ray Scattering of Injection-Molded Polymers: Anisotropic Structure and Mechanical Properties of Low-Density Polyethylene

Regularization of polynomial networks for image recognition

Effects of Head-Tracking Artefacts on Externalization and Localization in Azimuth With Binaural Wearable Devices

Near-wall hemodynamic parameters quantification in in vitro intracranial aneurysms with 7 T PC-MRI