Publications related to FST-based Reconstruction of 3D-models from Non-Uniformly Sampled Datasets on the Sphere

Discrete choice modeling in the era of big data

The technological advancements of the past decades have allowed transforming an increasing part of our daily actions and decisions into storable data, leading to a radical change in the scale and scope of available data in relation to virtually any object ...

EPFL2024

Efficient Continual Finite-Sum Minimization

Volkan Cevher, Efstratios Panteleimon Skoulakis, Leello Tadesse Dadi

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

2024

Modeling friction and wear using an adaptive discrete-continuum coupling

Manon Eugénie Voisin--Leprince

When two objects slide against each other, wear and friction occur at their interface. The accumulation of wear forms what is commonly referred to as a ``third-body''. Understanding third-body evolution has significant applications in industry, where contr ...

EPFL2024

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

Yury Tsybin, Natalia Gasilova, Laure Menin, Anton Kozhinov, Konstantin Nagornov

Traditionally, mass spectrometry (MS) output is the ion abundance plotted versus the ionic mass-to-charge ratio m/z. While employing only commercially available equipment, Charge Determination Analysis (CHARDA) adds a third dimension to MS, estimating for ...

Amer Chemical Soc2024

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Lausanne2024

Demonstration of a sparse sensor placement technique to the limited diagnostic set in a fusion power plant

Artur Perek, Lorenzo Martinelli

DEMO will have a limited diagnostic set for optimization of reactor performance, and limited diagnostic coverage due to challenging reactor conditions. This poses challenges for control, especially for detachment control which is planned to be performed wi ...

Elsevier Science Sa2024

Iterative removal of sources to model the turbulent electromotive force

Abhijit Bhausaheb Bendre

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

Oxford Univ Press2024

Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Achille Mauri

We study the statistical mechanics and the equilibrium dynamics of a system of classical Heisenberg spins with frustrated interactions on a d -dimensional simple hypercubic lattice, in the limit of infinite dimensionality d -> infinity . In the analysis we ...

Amer Physical Soc2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

David Atienza Alonso, Miguel Peon Quiros, José Angel Miranda Calero, Hossein Taji

In wearable sensors, energy efficiency is crucial, particularly during phases where devices are not processing, but rather acquiring biosignals for subsequent analysis. This study focuses on improving the power consumption of wearables during these acquisi ...

2024

FST-based Reconstruction of 3D-models from Non-Uniformly Sampled Datasets on the Sphere

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Discrete choice modeling in the era of big data

Efficient Continual Finite-Sum Minimization

Modeling friction and wear using an adaptive discrete-continuum coupling

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

Residual-based attention in physics-informed neural networks

Demonstration of a sparse sensor placement technique to the limited diagnostic set in a fusion power plant

Iterative removal of sources to model the turbulent electromotive force

Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

Efficient Continual Finite-Sum Minimization

Residual-based attention in physics-informed neural networks

Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Discrete choice modeling in the era of big data

Adding Color to Mass Spectra of Biopolymers: Charge Determination Analysis (CHARDA) Assigns Charge State to Every Ion Peak

Modeling friction and wear using an adaptive discrete-continuum coupling

Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables

Demonstration of a sparse sensor placement technique to the limited diagnostic set in a fusion power plant

Iterative removal of sources to model the turbulent electromotive force

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems