Publications associées à From STEM-EDXS data to phase separation and quantification using physics-guided NMF

Publications associées (16)

Drone-Based Urban Traffic Monitoring and User Behavior Prediction

As urban populations continue to expand and vehicle density increases, the need for effective traffic monitoring and management becomes increasingly critical. Urban areas face significant challenges such as growing congestion, safety concerns, and parking ...

EPFL2025

High-resolution predictions of the coolant properties for the 3D PWR core with artificial neural networks based on CTF

Marianna Papadionysiou

PSI and North Carolina State University are developing a high-resolution multi-physics core solver for Pressurized Water Reactor (PWR) analysis in Cartesian geometry, using the neutron transport code nTRACER and two Machine Learning (ML) models providing t ...

2025

Superior Adhesion of Monolayer Amorphous Carbon to Copper

Oleg Yazyev, Ruslan Yamaletdinov, Hanning Zhang

The single‐atom thickness of graphene holds great potential for device scaling, but its effectiveness as a thin metal‐ion diffusion barrier in microelectronics and a corrosion barrier for plasmonic devices is compromised by weak van der Waals interactions ...

Wiley2025

Causality: fundamental principles and tools

Elise Hélène Dumas

This chapter aims to provide a gentle introduction to Causal Learning (CL), and motivation for its application to medical image analysis, seeking for more robustness against data and domain drifts, and a reliable tool to answer counterfactual questions and ...

Academic Press2025

Simplifying Source-Free Domain Adaptation for Object Detection: Effective Self-training Strategies and Performance Insights

Olga Fink, Florent Evariste Forest

This paper focuses on source-free domain adaptation for object detection in computer vision. This task is challenging and of great practical interest, due to the cost of obtaining annotated data sets for every new domain. Recent research has proposed vario ...

Springer Science and Business Media Deutschland GmbH2025

Almost exact recovery in noisy semi-supervised learning

Maximilien Claude Robert Dreveton

2024.Graph-based semi-supervised learning methods combine the graph structure and labeled data to classify unlabeled data. In this work, we study the effect of a noisy oracle on classification. In particular, we derive the maximum a posteriori (MAP) estima ...

2024

Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo

Henning Paul-Julius Stahlberg

With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While diff ...

CELL PRESS2024

Microporous transport layers facilitating low iridium loadings in polymer electrolyte water electrolysis

Manuel Guizar Sicairos

Minimizing the power-specific iridium loading in polymer electrolyte water electrolysis (PEWE) is essential for the commercialization and upscaling of this technology. However, decreasing the iridium loading can severely affect performance and stability. M ...

ROYAL SOC CHEMISTRY2024

Spontaneous Raman scattering as a probe of vibrational quantum coherence and plasmonic near-field

Valeria Vento

Spontaneous vibrational Raman scattering is a ubiquitous form of light-matter interaction whose description necessitates quantization of the electromagnetic field. It is usually considered an incoherent process since it stems from the fluctuations of the v ...

EPFL2024

Euclid preparation XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

Frédéric Courbin, Georges Meylan, Austin Chandler Peel

The Euclid mission is expected to image millions of galaxies at high resolution, providing an extensive dataset with which to study galaxy evolution. Because galaxy morphology is both a fundamental parameter and one that is hard to determine for large samp ...

2024

Probing the nature of the χc1(3872) state using radiative decays

Olivier Schneider, Aurelio Bay, Guido Haefeli, Tatsuya Nakada, Frédéric Blanc, Lesya Shchutska, Elena Graverini, Sebastian Schulte, Donal Patrick Hill, Marie Theres Christin Bachmayer, Serhii Cholak, Ettore Zaffaroni, Aravindhan Venkateswaran, Luis Miguel Garcia Martin, Vitalii Lisovskyi, Elisabeth Maria Niel, Federico Ronchetti, Radoslav Marchevski, Anni Matilda Kauniskangas, Dimitrios Kaminaris, Raphaël van Laak, Pierre Paul Louis Mayencourt, Brianna Leililani Thielen, Arnaud Merlin Gauthey, Gianluca Zunica, Abdul-Kerim Guseinov, Esteban Curras Rivera, Roberto Ribatti, Alexandre Brea Rodriguez, Rita De Sousa Ataíde Da Silva

Abstract: The radiative decays χc1(3872) → ψ(2S) γ and χc1(3872) → J/ψγ are used to probe the nature of the χc1(3872) state using proton-proton collision data collected with the LHCb detector, corresponding to an integrated luminosity of 9 fb−1. Using the ...

Springer Nature2024

Programming nonlinear propagation for efficient optical learning machines

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç, Ugur Tegin, Ilker Oguz, Mustafa Yildirim, Carlo Gigli, Jih-Liang Hsieh

The ever-increasing demand for training and inferring with larger machine-learning models requires more efficient hardware solutions due to limitations such as power dissipation and scalability. Optics is a promising contender for providing lower power com ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

Coupling Free Electrons and Cavity Photons in a Transmission Electron Microscope

Tobias Kippenberg, Junqiu Liu, Rui Ning Wang, Arslan Sajid Raja, Guanhao Huang, Zheru Qiu, Yujia Yang

We couple free electrons to the optical modes of a photonic microring resonator. Inelastic electron scattering leads to the generation of cavity photons, correlated to the electrons in time and energy loss. ...

Institute of Electrical and Electronics Engineers Inc.2024

Forward-forward training of an optical neural network

Demetri Psaltis, Christophe Moser, Niyazi Ulas Dinç, Ilker Oguz, Mustafa Yildirim, Jih-Liang Hsieh

Neural networks (NNs) have demonstrated remarkable capabilities in various tasks, but their computation-intensive nature demands faster and more energy-efficient hardware implementations. Optics-based platforms, using technologies such as silicon photonics ...

Optica Publishing Group2023

AmadeusGPT: a natural language interface for interactive animal behavioral analysis

Alexander Mathis, Mackenzie Mathis, Shaokai Ye, Jessy Lauer, Mu Zhou

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of anim ...

2023

Stochastic Approximation of Variational Quantum Imaginary Time Evolution

Giuseppe Carleo

The imaginary-time evolution of quantum states is integral to various fields, ranging from natural sciences to classical optimization or machine learning. Since simulating quantum imaginary-time evolution generally requires storing an exponentially large w ...

Institute of Electrical and Electronics Engineers Inc.2023