Publications related to Image shift correction, noise analysis, and model fitting of (cathodo-)luminescence hyperspectral maps

Related publications (16)

Machine learning enhanced atom probe tomography analysis

Atom probe tomography (APT) is a burgeoning characterization technique that provides compositional mapping of materials in three-dimensions at near-atomic scale. Since its significant expansion in the past 30 years, we estimate that one million APT dataset ...

2026

Monomeric Fe in Six-Membered Rings at Work: Operando Spectroscopy of Nitrous Oxide Activation and Decomposition over Fe-Exchanged Zeolites

Oliver Kröcher, Daniel Camilo Cano Blanco

The heterogeneous speciation of ion-exchanged zeolites hinders a rational understanding of their reactivity. This is particularly the case for Fecontaining zeolites that are widely used in both the activation and decomposition of N 2 O. Herein, we explored ...

American Chemical Society (ACS)2025

synMARSS—An End-To-End Platform for the Parametric Generation of Synthetic In Vivo Magnetic Resonance Spectra

André Döring

Synthetic magnetic resonance spectra (MRS) are mathematically generated spectra which can be used to investigate the assumptions of data analysis strategies, optimize experimental design, and as training data for the development and validation of machine l ...

2025

Robustly Learning Regions of Attraction From Fixed Data

Colin Neil Jones

While stability analysis is a mainstay for control science, especially computing regions of attraction of equilibrium points, until recently most stability analysis tools always required explicit knowledge of the model or a high-fidelity simulator represen ...

2025

Squaraine Dyes for Organic Photomultiplication Photodetectors with 220% External Quantum Efficiency at 1240 nm

João Pedro Ferreira Assunção, Frank Nüesch, Elodie Didier

Near-infrared (NIR) light detection at wavelengths lambda > 1100 nm is essential in modern science and technology. Emerging organic semiconductors are promising for solution-processed, flexible, and large-area NIR organic photodetectors (OPDs), but only a ...

WILEY2025

Advancements and Prospects of Near-infrared-light Driven Co2 Reduction Reaction

Jiaqi Xu

In the realm of photoconversion of CO2 into high-value chemicals, the importance of near-infrared (NIR) light is gradually gaining recognition. Relative to ultraviolet (UV) and visible light, NIR light (700-2500 nm), accounting for ca. 50% of solar energy, ...

Royal Society of Chemistry2025

Hadamard product in deep learning: Introduction, Advances and Challenges

Volkan Cevher, Yongtao Wu

While convolution and self-attention mechanisms have dominated architectural design in deep learning, this survey examines a fundamental yet understudied primitive: the Hadamard product. Despite its widespread implementation across various applications, th ...

2025

Neural networks trained with SGD learn distributions of increasing complexity

Maria Refinetti

The uncanny ability of over-parameterised neural networks to generalise well has been explained using various ‘simplicity biases’. These theories postulate that neural networks avoid overfitting by first fitting simple, linear classifiers before learning m ...

2025

Representing and machine learning complex electronic-structure properties of materials

Austin Jacob Zadoks

The rise of high-throughput first-principles calculations of materials since the turn of the millennium has gifted the fields of physics, quantum chemistry, and materials science with a mountainous and ever-growing pile of data ready to be mined for hidden ...

EPFL2025

The Galaxy Activity, Torus, and Outflow Survey (GATOS) VI. Black hole mass estimation using machine learning

Rémi Henri Philippe Poitevineau

The detailed feeding and feedback mechanisms of active galactic nuclei (AGNs) are not yet well known. For low-luminosity AGNs, obscured AGNs, and late-type galaxies, the masses of their central black holes (BH) are difficult to determine precisely. Our goa ...

EDP SCIENCES S A2025

Electronic structure of Bi2 Ir2 O7 probed by resonant inelastic x-ray scattering at the oxygen K edge: Metallicity, hybridization, and electronic correlations

Henrik Moodysson Rønnow

The electronic structure of metallic Bi2Ir2O7 has been investigated by a combination of soft x-ray absorption spectroscopy, x-ray emission spectroscopy (XES), and resonant inelastic x-ray scattering (RIXS) in the vicinity of the oxygen K edge. The O K-edge ...

2025

A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs

Florent Gérard Krzakala, Bruno Loureiro, Matteo Vilucchio

This work investigates adversarial training in the context of margin-based linear classifiers in the high-dimensional regime where the dimension d and the number of data points n diverge with a fixed ratio α = n/d. We introduce a tractable mathematical mod ...

2025

Quantifying electronic and geometric effects on the activity of platinum catalysts for water-gas shift

Giovanni Pizzi

The unique catalytic activity of small nanoparticles can be attributed to their distinctive electronic structure and/or their ability to expose sites with a unique geometry. Quantifying and distinguishing the contributions of these effects to catalytic per ...

2025

Probing the Formation of Nonlinear Optical States with Free Electrons

Tobias Kippenberg, Rui Ning Wang, Arslan Sajid Raja, Guanhao Huang, Zheru Qiu, Alexey Tikan, Aleksandr Tusnin, Yujia Yang

Combining nonlinear integrated photonics with electron microscopy, we probe the formation of optical dissipative structures in Si3N4 microresonators with free electrons and find unique spectral fingerprints in the electron spectrum that enable new electron ...

Institute of Electrical and Electronics Engineers Inc.2024

Function Learning with Financial Applications

Paolo Colusso

This thesis sets itself the goal of investigating function learning approaches. The topic is extremely relevant today, since the abundance of data, jointly with the technological progress which has enhanced computing power, now allow to represent functions ...

EPFL2024

Unsupervised quality monitoring of metal additive manufacturing using Bayesian adaptive resonance

Patrik Willi Hoffmann

Metal additive manufacturing is a recent breakthrough technology that promises automated production of complex geometric shapes at low operating costs. However, its potential is not yet fully exploited due to the low reproducibility of quality in mass prod ...

CELL PRESS2024