Publications associées à Rapid prediction of phonon density of states by crystal attention graph neural network and high-throughput screening of candidate substrates for wide bandgap electronic cooling

Publications associées (13)

Mass-zero constrained dynamics for density functional based ab-initio MD

The goal of this thesis is to develop the formalism for the extension of a newly developed approach to adiabatic quantum molecular dynamics, the mass-zero constrained dynamics (MaZe) method, to the framework of Kohn-Sham density functional theory (KS-DFT). ...

EPFL2025

Fully data-driven and modular building thermal control with physically consistent modeling

Benjamin Bejar Haro, Carl Pierre Jacques Remlinger

Machine learning has experienced significant growth in the smart building sector, whether for building modeling or energy management. Data-driven approaches leverage available measurements to bypass the slow and costly calibration of physics-based models, ...

2025

Machine learning enhanced tomographic reconstruction for multispectral imaging on TCV

Basil Duval, Artur Perek

A multispectral camera setup is used to infer a 2D map of plasma parameters in a tokamak from spectral emissions. However, the light measured by these cameras is line integrated in the toroidal direction, whereas emissivities on the poloidal plane are nece ...

2025

From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

Lucas Maximilian Stoffl

Accurately measuring behavior is critical to understanding brain function. While traditional behavioral analysis has relied on human observation and manual processing, advances in machine learning and computer vision have begun to automate the field. This ...

EPFL2025

Nonlocal metamaterials and metasurfaces

Romain Christophe Rémy Fleury, Yihong Chen

The aim of rationally designed composites called metamaterials or metasurfaces is to achieve effective properties that go beyond those of their constituent parts. For periodic architectures, the design can draw on concepts from solid-state physics, such as ...

Springer Science and Business Media LLC2025

Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers

Olga Fink, Gaëtan Michel Frusque, Florent Evariste Forest

Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds. While these parameters are crucial, they only cover a small subset of malfun ...

2025

Roadmap on data-centric materials science

Ye Wei

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift toward ...

2024

NNG-Mix: Improving Semi-Supervised Anomaly Detection with Pseudo-Anomaly Generation

Olga Fink, Gaëtan Michel Frusque

Anomaly detection (AD) is essential in identifying rare and often critical events in complex systems, finding applications in fields such as network intrusion detection, financial fraud detection, and fault detection in infrastructure and industrial system ...

2024

Prediction of mycotoxin response of DNA-wrapped nanotube sensor with machine learning

Ardemis Anoush Boghossian, Sara Behjati, Sayyed Hashem Sajjadi, Yahya Rabbani

DNA-wrapped single-walled carbon nanotubes (DNA-SWCNTs) have demonstrated great versatility as optical sensors. SWCNTs emit a near-infrared fluorescence that is responsive to the slightest changes in their environment, enabling the creation of sensors that ...

2023

Data analysis techniques for the visualization and classification of historical vehicle engines' health status using data-driven solutions

Alejandro Roda Buch

In the field of cultural heritage, the use of non-destructive techniques to determine the state ofconservation of an artifact is of the utmost importance, to avoid damage to the object itself. In this paper, we present a data pipeline and several machine l ...

ASSOC PROFISSIONAL CONSERVADORES-RESTAURADORES PORTUGAL2023

Origin of metallic-like behavior in disordered carbon nano-onions

Oleg Yazyev, Kristians Cernevics

Carbon nano-onions are a class of nanomaterials that can exhibit long electron spin relaxation times at room temperature and thus hold promise as potential building blocks for spintronics and quantum information processing devices. Despite first being synt ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Response of magnesium microcrystals to c-axis compression and contraction loadings at low and high strain rates

Roland Logé, Cyril Cayron

In this work, 99.999% pure magnesium (Mg) single microcrystals have been deformed in [0001] compression (c-axis compression) and [10 (1) over bar0] tension (c-axis contraction) conditions at room temperature and under loading rates ranging from 5 x 10(-4) ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Machine Learning Models for Mycobacterium tuberculosis In Vitro Activity: Prediction and Target Visualization

Anthony Vocat

Tuberculosis (TB) is a major global health challenge, with approximately 1.4 million deaths per year. There is still a need to develop novel treatments for patients infected with Mycobacterium tuberculosis (Mtb). There have been many large-scale phenotypic ...

AMER CHEMICAL SOC2022