Publications related to Exploring Local Modifications for Constrained Meshes

Related publications (35)

Testing Theories of the Glass Transition with the Same Liquid but Many Kinetic Rules

We study the glass transition by exploring a broad class of kinetic rules that can significantly modify the normal dynamics of supercooled liquids while maintaining thermal equilibrium. Beyond the usual dynamics of liquids, this class includes dynamics in ...

Amer Physical Soc2024

Towards Trustworthy Deep Learning for Image Reconstruction

Alexis Marie Frederic Goujon

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

DARTS-NETGAB: DESIGN AUTOMATION AND REAL-TIME SIMULATION USING NEURAL NETWORKS ENSEMBLES FOR TURBOCOMPRESSORS ON GAS-BEARINGS

Jürg Alexander Schiffmann, Soheyl Massoudi, Timothy Horvath, Joseph Bejjani

In the domain of engineering design, where efficiency in simulation and precision in modeling are paramount, this study introduces DARTS-NETGAB, a pioneering platform uniquely designed for real-time simulation and automated design. Specifically tailored fo ...

American Society of Mechanical Engineers (ASME)2024

FIRST COMPARISON STUDIES IN DYNAMIC APERTURE FOR NESTED MAGNETS AND BASELINE LATTICE IN THE FCC-ee

Tatiana Pieloni, Mike Seidel, Léon Van Riesen-Haupt, Cristobal Miguel Garcia Jaimes

A significant project such as the FCC-ee (with 91.17 km circumference) entails numerous challenges to ensure the stability and performance of the machine. In the pursuit of contributing to the improvement of energy consumption during its operation, the exp ...

JACoW2024

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

Parental status and markers of brain and cellular age: A 3D convolutional network and classification study

Donal Patrick Hill

Recent research shows prominent effects of pregnancy and the parenthood transition on structural brain characteristics in humans. Here, we present a comprehensive study of how parental status and number of children born/fathered links to markers of brain a ...

Pergamon-Elsevier Science Ltd2024

Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation

Haoqi Wang

We generalize the class vectors found in neural networks to linear subspaces (i.e., points in the Grassmann manifold) and show that the Grassmann Class Representation (GCR) enables simultaneous improvement in accuracy and feature transferability. In GCR, e ...

Ieee Computer Soc2023

Distributed Lossy Computation with Structured Codes: From Discrete to Continuous Sources

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

This paper considers the problem of distributed lossy compression where the goal is to recover one or more linear combinations of the sources at the decoder, subject to distortion constraints. For certain configurations, it is known that codes with algebra ...

2023

Dynamical Low-Rank Approximation for Stochastic Differential Equations

Fabio Nobile, Yoshihito Kazashi, Fabio Zoccolan

In this paper, we set the mathematical foundations of the Dynamical Low-Rank Approximation (DLRA) method for stochastic differential equations (SDEs). DLRA aims at approximating the solution as a linear combination of a small number of basis vectors with r ...

American Mathematical Society (AMS)2025

Non-intrusive data-driven reduced-order modeling for time-dependent parametrized problems

Jan Sickmann Hesthaven, Junming Duan

Reduced-order models are indispensable for multi-query or real-time problems. However, there are still many challenges to constructing efficient ROMs for time-dependent parametrized problems. Using a linear reduced space is inefficient for time-dependent n ...

Academic Press Inc Elsevier Science2023

Short homology bases for hyperelliptic hyperbolic surfaces

Jürgpeter Buser

Given a hyperelliptic hyperbolic surface S of genus g >= 2, we find bounds on the lengths of homologically independent loops on S. As a consequence, we show that for any lambda is an element of (0, 1) there exists a constant N(lambda) such that every such ...

Hebrew Univ Magnes Press2023

Density estimation in RKHS with application to Korobov spaces in high dimensions

Fabio Nobile, Yoshihito Kazashi

A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

2023

Character of Electronic States in the Transport Gap of Molecules on Surfaces

Klaus Kern, Abhishek Grewal

We report on scanningtunneling microscopy (STM) topographs ofindividual metal phthalocyanines (MPc) on a thin salt (NaCl) filmadsorbed on a gold substrate, at tunneling energies within the molecule'selectronic transport gap. Theoretical models of increasin ...

AMER CHEMICAL SOC2023

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023

Systematic design of a multi-input multi-output controller by model-based decoupling: a demonstration on TCV using multi-species gas injection

Basil Duval, Christian Gabriel Theiler, Cristian Galperti, Artur Perek

In this paper, we present the first results of a systematically designed multi-input multi-output gas-injection controller on Tokamak a Configuration Variable (TCV). We demonstrate the simultaneous real-time control of the NII emission front position and l ...

IOP Publishing Ltd2023

The hunt for the Karman 'constant' revisited

Peter Monkewitz

The log law of the wall, joining the inner, near-wall mean velocity profile (MVP) in wall-bounded turbulent flows to the outer region, has been a permanent fixture of turbulence research for over hundred years, but there is still no general agreement on th ...

Cambridge University Press2023

Linear and nonlinear substructured Restricted Additive Schwarz iterations and preconditioning

Tommaso Vanzan

Iterative substructuring Domain Decomposition (DD) methods have been extensively studied, and they are usually associated with nonoverlapping decompositions. It is less known that classical overlapping DD methods can also be formulated in substructured for ...

2022

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Le Nguyen Hoang, Sadegh Farhadkhani, John Stephan

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023

Global Mapping of Potential and Climatic Plant‐Available Soil Water

Dani Or, Sara Bonetti

The estimation of plant-available soil water (PASW) is essential to quantify transpiration fluxes, the onset of heatwaves, irrigation water management, land-use decisions, vegetation ecology, and land surface memory in climate models. PASW is the amount of ...

2023

Identifiability and Generalizability from Multiple Experts in Inverse Reinforcement Learning

Volkan Cevher, Luca Viano, Paul Thierry Yves Rolland, Boris Nikolov

While Reinforcement Learning (RL) aims to train an agent from a reward function in a given environment, Inverse Reinforcement Learning (IRL) seeks to recover the reward function from observing an expert’s behavior. It is well known that, in general, variou ...

2022