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Publications associées (27)

Sparse autoregressive neural networks for classical spin systems

Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Iop Publishing Ltd2024

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli, Paolo Pegolo

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Frontiers Media Sa2024

Learning Physics-Consistent Particle Interactions

Olga Fink, David Simon Kammer

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hi ...

Oxford University Press2023

Game changers in science and technology- now and beyond

Yahya Mohammadzadeh

The recent devastating pandemic has drastically reminded humanity of the importance of constant scientific and technological progress. A strong interdisciplinary dialogue between academic and industrial scientists of various specialties, entrepreneurs, man ...

ELSEVIER SCIENCE INC2023

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Olga Fink

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...

2023

Generating Controlled Physics-Informed Time-to-failure Trajectories for Prognostics in Unseen Operational Conditions

Olga Fink

Research Publishing2023

Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-Based Filters

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency between any known underlying physical laws and a data-driven decision-making process, preprocessin ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Scientific rewards for biomedical specialization are large and persistent

Gaétan Jean A de Rassenfosse, Orion B Penner, Kyle William Higham

Background While specialization plays an essential role in how scientific research is pursued, we understand little about its effects on a researcher's impact and career. In particular, the extent to which one specializes within their chosen fields likely ...

BMC2022

High-order accurate entropy stable adaptive moving mesh finite difference schemes for special relativistic (magneto)hydrodynamics

Junming Duan

This paper develops high-order accurate entropy stable (ES) adaptive moving mesh finite difference schemes for the two- and three-dimensional special relativistic hydrodynamic (RHD) and magnetohydrodynamic (RMHD) equations, which is the high-order accurate ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

High-order accurate entropy stable adaptive moving mesh finite difference schemes for (multi-component) compressible Euler equations with the stiffened equation of state

Junming Duan

This paper extends the high-order entropy stable (ES) adaptive moving mesh finite difference schemes developed in Duan and Tang (2022) to the two- and three-dimensional (multi-component) compressible Euler equations with the stiffened equation of state (EO ...

Elsevier Science Sa2022

Finding symmetry breaking order parameters with Euclidean neural networks

Mario Geiger

Curie's principle states that "when effects show certain asymmetry, this asymmetry must be found in the causes that gave rise to them." We demonstrate that symmetry equivariant neural networks uphold Curie's principle and can be used to articulate many sym ...

AMER PHYSICAL SOC2021

Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks

Jan Sickmann Hesthaven, Deep Ray, Lukas Schwander

While a nonlinear viscosity is used widely to control oscillations when solving conservation laws using high-order elements based methods, such techniques are less straightforward to apply in global spectral methods since a local estimate of the solution r ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

Silver Nanomaterials in Contemporary Molecular Physiology Research

Sandor Kasas

Silver nanoparticles have numerous potential applications in engineering, industry, biology and medicine. Because of their unique chemical properties, they have become the focus of many research teams all over the world. Silver nanoparticles may exhibit si ...

BENTHAM SCIENCE PUBL LTD2020

Adaptive Laser Welding Control: A Reinforcement Learning Approach

Giulio Masinelli, Silvio Zanoli

Despite extensive research efforts in the field of laser welding, the imperfect repeatability of the weld quality still represents an open topic. Indeed, the inherent complexity of the underlying physical phenomena prevents the implementation of an effecti ...

2020

From the Principle of Inertia to the Death Drive: The Influence of the Second Law of Thermodynamics on the Freudian Theory of the Psychical Apparatus

Pierre Magistretti, Jean-Philippe Ansermet

In the Freudian theory of the psychical apparatus, the introduction from the 1920s onward of the second drive dualism appears as a major turning point. The idea of a "death drive," first expressed in Beyond the Pleasure Principle (Freud, 1920), is generall ...

Frontiers Media2020

Analyzing four decades of literature on urban planning studies in Africa (1980–2020)

Jérôme Chenal, Rémi Jaligot, Armel Firmin Kemajou Mbianda, Akuto Akpedze Konou

Although rapid population growth will give them a significant weight in global urbanization by the middle of the century, African cities remain little known. As a result, they are essentially outside the global intellectual arena on urban issues, which jus ...

2020

Training Algorithms for Multiple Object Tracking

Andrii Maksai

Multiple object tracking is a crucial Computer Vision Task. It aims at locating objects of interest in the image sequences, maintaining their identities, and identifying their trajectories over time. A large portion of current research focuses on tracking ...

EPFL2019

Unravelling the precipitation pathway of biorelevant minerals: from fundamental studies to biomedical applications

Agnese Carino

The formation pathway of biominerals archetypes, namely calcium carbonate (CaC) and calcium phosphates (CaPs), was investigated using a multidisciplinary approach. The time-resolved analytical data were collected using a controlled-composition method and i ...

EPFL2018

Upscaling the evolution of snow microstructure : from 4D image analysis to rigorous models

Quirien Eibhilín Krol

Snow microstructure and its evolution play an important role for various applications of snow physics in cryospheric sciences. The main modes of microstructure evolution in snow are referred to as isothermal and temperature gradient metamorphism. The forme ...

EPFL2017

A view on global urbanization : spatial networks, urban scaling and remote sensing

Emanuele Strano

It is widely recognized that global urbanization is one the most urgent issue of our time. Any problem related to global issues, such as climate change, social and environmental sustainability and the future of our society, is somehow related to cities and ...

EPFL2016