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Structural topology exploration through policy-based generation of equilibrium representations

Publications associées (29)

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

SPRINGER2023

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Backtracking Dynamical Cavity Method

Lenka Zdeborová, Freya Behrens, Barbora Hudcová

The cavity method is one of the cornerstones of the statistical physics of disordered systems such as spin glasses and other complex systems. It is able to analytically and asymptotically exactly describe the equilibrium properties of a broad range of mode ...

American Physical Society2023

Bending and Stretching in a Narrow Ribbon of Nematic Polymer Networks

Harmeet Singh

We study the spontaneous out-of-plane bending of a planar untwisted ribbon composed of nematic polymer networks activated by a change in temperature. Our theory accounts for both stretching and bending energies, which compete to establish equilibrium. We s ...

SPRINGER2023

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

Olga Fink, Chao Hu, Sayan Ghosh

SPRINGER2023

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Jürg Alexander Schiffmann, Soheyl Massoudi, Cyril Picard

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

ASME Amer Soc Mechanical Engineers2023

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Pergamon-Elsevier Science Ltd2023

Enriching the Computational Toolbox for Organocatalysis

Simone Gallarati

Organocatalysis has evolved significantly over the last decades, becoming a pillar of synthetic chemistry, but traditional theoretical approaches based on quantum mechanical computations to investigate reaction mechanisms and provide rationalizations of ca ...

EPFL2023

Stochastic adaptive resampling for the estimation of discrete choice models

Michel Bierlaire, Nicola Marco Ortelli, Matthieu Marie Cochon de Lapparent

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni, Elena Losanno, Luca Pierantoni

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

IOP Publishing Ltd2023

Growth and investigation of Argon thin films adsorbed on graphite by means of Ultrafast Electron Diffraction

Paolo Usai

Starting from our big universe to the microscopic world, phase transitions play an important role in nature. Just after the Big Bang our universe experienced multiple phase transitions, from high-temperature plasma to the matter we know today. Phase transi ...

EPFL2023

Page 3 sur 3

Backtracking Dynamical Cavity Method

Lenka Zdeborová, Freya Behrens, Barbora Hudcová

American Physical Society2023

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Jürg Alexander Schiffmann, Soheyl Massoudi, Cyril Picard

ASME Amer Soc Mechanical Engineers2023

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

Pergamon-Elsevier Science Ltd2023

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni, Elena Losanno, Luca Pierantoni

IOP Publishing Ltd2023

Growth and investigation of Argon thin films adsorbed on graphite by means of Ultrafast Electron Diffraction

Paolo Usai

EPFL2023