Publications associées à An artificial neural network approach to bifurcating phenomena in computational fluid dynamics

Publications associées (15)

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulatio ...

2024

Privacy-Preserving Image Acquisition for Neural Vision Systems

Pascal Frossard, Yamin Sepehri

Preserving privacy is a growing concern in our society where cameras are ubiquitous. In this work, we propose a trainable image acquisition method that removes the sensitive information in the optical domain before it reaches the image sensor. The method b ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Sparse Attacks for Manipulating Explanations in Deep Neural Network Models

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Michail Vlachos

We investigate methods for manipulating classifier explanations while keeping the predictions unchanged. Our focus is on using a sparse attack, which seeks to alter only a minimal number of input features. We present an efficient and novel algorithm for co ...

Ieee Computer Soc2023

Adversarial Training Should Be Cast As a Non-Zero-Sum Game

Volkan Cevher, Seyed Hamed Hassani, Fabian Ricardo Latorre Gomez

One prominent approach toward resolving the adversarial vulnerability of deep neural networks is the two-player zero-sum paradigm of adversarial training, in which predictors are trained against adversarially-chosen perturbations of data. Despite the promi ...

2023

Time-encoded multiplication-free spiking neural networks: application to data classification tasks

Ana Stanojevic

Spiking neural networks (SNNs) are mimicking computationally powerful biologically inspired models in which neurons communicate through sequences of spikes, regarded here as sparse binary sequences of zeros and ones. In neuroscience it is conjectured that ...

2022

Role of stochastic noise and generalization error in the time propagation of neural-network quantum states

Giuseppe Carleo

Neural-network quantum states (NQS) have been shown to be a suitable variational ansatz to simulate out-of-equilibrium dynamics in two-dimensional systems using timedependent variational Monte Carlo (t-VMC). In particular, stable and accurate time propagat ...

SCIPOST FOUNDATION2022

Physico-chemical properties prediction of hydrochar in macroalgae Sargassum horneri hydrothermal carbonisation

Farzaneh Talebkeikhah, Mohsen Talebkeikhah

This study evaluates and compares several machine learning methods on the effects of different parameters in the hydrothermal carbonisation (HTC) process of macroalgae Sargassum horneri. Reaction temperature, residence time, biomass particle size, the amou ...

TAYLOR & FRANCIS LTD2021

Self-similar invariant solution in the near-wall region of a turbulent boundary layer at asymptotically high Reynolds numbers

Tobias Schneider, Sajjad Azimi

At sufficiently high Reynolds numbers, shear-flow turbulence close to a wall acquires universal properties. When length and velocity are rescaled by appropriate characteristic scales of the turbulent flow and thereby measured in inner units, the statistica ...

Cambridge University Press2020

Receptor-induced transient responses in cells with oscillatory actin dynamics

Jose Negrete Jr

Living cells adjust their sensing and migratory machinery in response to changes in their environment. In this work, we show that cells of the social amoeba Dictyostelium discoideum modulate the dynamical state of their actin cytoskeleton in response to an ...

AMER PHYSICAL SOC2020

From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems

Nadia Barbara Figueroa Fernandez

Humans have a remarkable way of learning, adapting and mastering new manipulation tasks. With the current advances in Machine Learning (ML), the promise of having robots with such capabilities seems to be on the cusp of reality. Transferring human-level sk ...

EPFL2019

Experimental and numerical study on wave-impact on buildings

Giovanni De Cesare, Michael Pfister, Davide Wüthrich

Unsteady flows such as tsunamis, impulse waves and dam-break waves can lead to damages and human losses. Hence, specific research to limit casualties and reconstruction costs is needed. The complexity of the phenomena involved suggests that a hybrid experi ...

2019

A one-dimensional viscoelastic and viscoplastic constitutive approach to modeling the delayed behavior of clay and organic soils

Aldo Madaschi

Accurate modeling of the time-dependent behavior of geomaterials is of great importance in a number of engineering structures interacting with soft, highly compressible clay layers or with organic clays and peats. In this work, a uniaxial constitutive mode ...

Springer Verlag2017

Learning Approach to Optical Tomography

Demetri Psaltis, Michaël Unser, Ulugbek Kamilov, Cédric René Jean Vonesch, Alexandre Goy

Optical tomography has been widely investigated for biomedical imaging applications. In recent years optical tomography has been combined with digital holography and has been employed to produce high-quality images of phase objects such as cells. In this p ...

Optical Soc Amer2015

Distributed real-time dynamic security assessment using intelligent techniques

Maher Kayal, Sidi-Rachid Cherkaoui, Theodoros Kyriakidis

In real time scenario, transmission (of power) in power systems may not be always ideal i.e. they may be interrupted. As a result, the synchronization among the power generating modules may be lost. Loss of synchronization has a direct effect on the stabil ...

IEEE2013

Experimental Aeroelastic Investigation of Vibrating Turbine Blade Clusters

Peter Ott, Achim Zanker

The presented work consists of the presentation and discussion of unsteady experimental results of controlled vibration measurements for two single-blade and two cluster test cases subjected to the same subsonic flow conditions. The experiments were perfor ...

Lappeenranta University of Technology2013