Publications associées à Linear Estimation of Deterministic Accelerometer Errors

Publications associées (11)

Secure and federated genome-wide association studies for biobank-scale datasets

Sharing data across institutions for genome-wide association studies (GWAS) would enhance the discovery of genetic variation linked to health and disease1,2. However, existing data-sharing regulations limit the scope of such collaborations3. Although crypt ...

NATURE PORTFOLIO2025

Randomized Block Gram–Schmidt Process for the Solution of Linear Systems and Eigenvalue Problems

Laura Grigori

Society for Industrial & Applied Mathematics (SIAM)2025

Decoding the Discourse: Analyzing the Linguistic Features and Strategies Behind the Querdenken Movement's COVID-19 Narrative

Cheng Pan

This study analyzes the linguistic rhetorical strategies utilized by the German-speaking Querdenken movement's alternative media during the COVID-19 pandemic. Employing a critical discourse analysis (CDA) framework, we examine articles from alternative med ...

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD2025

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Ismail Nejjar

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

EPFL2025

Mesh d-refinement: a data-based computational framework to account for complex material response

Jean-François Molinari, Antonio Joaquin Garcia Suarez, Sacha Zenon Wattel

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...

2023

Compressed Distributed Regression over Adaptive Networks

Ali H. Sayed

We examine the learning performance achievable by a network of agents that solve a distributed regression problem using the recently proposed ACTC (Adapt-Compress-Then-Combine) diffusion strategy. The agents operate under communication constraints: they ar ...

IEEE2023

Biomechanical Ambulatory Assessment of 3D Knee Angle Using Novel Inertial Sensor-Based Technique

Lai Kuan Tham, Kamiar Aminian

Three-dimensional (3D) knee angle measurement is one of the key measures in human gait analysis. Inertial sensor capable of measuring joint motion under unconstrained conditions is a practical tool for clinical evaluation and rehabilitation. An inertial me ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Model order reduction of flow based on a modular geometrical approximation of blood vessels

Simone Deparis, Luca Pegolotti

We are interested in a reduced order method for the efficient simulation of blood flow in arteries. The blood dynamics is modeled by means of the incompressible Navier–Stokes equations. Our algorithm is based on an approximated domain-decomposition of the ...

2021

Adaptive hot water production based on Supervised Learning

Alexandre Massoud Alahi, Dolaana Khovalyg, Amirreza Heidari

A major challenge in the common approach of hot water generation in residential houses lies in the highly stochastic nature of domestic hot water (DHW) demand. Learning hot water use behavior enables water heating systems to continuously adapt to the stoch ...

2021

Non-linear modelling of saturated internal and external MHD instabilities in tokamaks

Andreas Kleiner

Macroscopic instabilities and their unfavourable effects on plasma confinement pose a central challenge for the development of reactor relevant tokamak scenarios. Some promising operation scenarios feature extended regions of low magnetic shear. These are ...

EPFL2019

Electron density learning of non-covalent systems

Michele Ceriotti, Anne-Clémence Corminboeuf, Alberto Fabrizio, Benjamin André René Meyer, Andrea Grisafi

Chemists continuously harvest the power of non-covalent interactions to control phenomena in both the micro- and macroscopic worlds. From the quantum chemical perspective, the strategies essentially rely upon an in-depth understanding of the physical origi ...

2019