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

Publications associées (14)

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Anne-Clémence Corminboeuf, Friedrich Eisenbrand, Rubén Laplaza Solanas, Puck Elisabeth van Gerwen, Ksenia Briling, Jan Weinreich, Matthieu Nicolas Haeberle

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

IOP Publishing Ltd2025

Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study

Philipp Jürgen Schneider

Online communities play a critical role in shaping societal discourse and influencing collective behavior in the real world. The tendency for people to connect with others who share similar characteristics and views, known as homophily, plays a key role in ...

ACM2025

Intelligent Support Engages Writers Through Relevant Cognitive Processes

Seyed Parsa Neshaei

Student peer review writing is prevalent and important in education for fostering critical thinking and learning motivation. However, it often entails challenges such as high effort and writer's block. Leaving students unsupported may thus diminish the eff ...

Association for Computing Machinery2024

Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes

Tanja Christina Käser Jacober, Antoine Bosselut, Thiemo Wambsganss, Seyed Parsa Neshaei, Jibril Albachir Frej, Paola Mejia Domenzain, Luca Mouchel, Tatjana Nazaretsky

Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input ...

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

Data-driven models in fusion exhaust: AI methods and perspectives

Yoeri Renier Johannes Poels

A review is given on the highlights of a scatter-shot approach of developing machine-learning methods and artificial neural networks based fast predictors for the application to fusion exhaust. The aim is to enable and facilitate optimized and improved mod ...

IOP Publishing Ltd2024

Improving Group Testing via Gradient Descent

Pavlos Nikolopoulos

We study the problem of group testing with non-identical, independent priors. So far, the pooling strategies that have been proposed in the literature take the following approach: a hand-crafted test design along with a decoding strategy is proposed, and g ...

2024

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

Multi-IVE: Privacy Enhancement of Multiple Soft-Biometrics in Face Embeddings

Sébastien Marcel, Hatef Otroshi Shahreza

This study focuses on the protection of soft-biometric attributes related to the demographic information of individuals that can be extracted from compact representations of face images, called embeddings. We consider a state-ofthe-art technology for soft- ...

IEEE COMPUTER SOC2023

A unified stochastic approximation framework for learning in games

Volkan Cevher

We develop a flexible stochastic approximation framework for analyzing the long-run behavior of learning in games (both continuous and finite). The proposed analysis template incorporates a wide array of popular learning algorithms, including gradient-base ...

Springer Science and Business Media LLC2023

Design, prototyping, and thermo-mechanical modelling of a neutron spallation target impacted by high-energy proton-beam pulses in the n_TOF facility at CERN

Raffaele Esposito

This manuscript describes the design work and the R&D activities carried out for the third-generation neutron production target in the neutron Time-Of-Flight (n_TOF) facility at the European Laboratory for Particle Physics (CERN). The facility is composed ...

EPFL2022

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Mahsa Shoaran, Bingzhao Zhu

The researchers used a machine-learning classification approach to better understand neurological features associated with periods of wayfinding uncertainty. The participants (n = 30) were asked to complete wayfinding tasks of varying difficulty in a virtu ...

ELSEVIER SCI LTD2022

Ontology-based system to support industrial system design for aircraft assembly

Dimitrios Kyritsis, Jinzhi Lu

The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces between different digital tools, leading to extra development time and costs ...

ELSEVIER2022

Quadrature-free immersed isogeometric analysis

Pablo Antolin Sanchez, Thibaut Hirschler

This paper presents a novel method for solving partial differential equations on three-dimensional CAD geometries by means of immersed isogeometric discretizations that do not require quadrature schemes. It relies on a newly developed technique for the eva ...

SPRINGER2022