Machine learning with multimode fibers

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (30)

Page 2 sur 2

Manipulation of Strongly Interacting Solitons in Optical Fiber Experiments

Andrey Gelash

The model underlying physics of guiding light in single-mode fibers-the one-dimensional nonlinear Schr & ouml;dinger equation (NLSE)-reveals a remarkable balance of the fiber dispersion and nonlinearity, leading to the existence of optical solitons. With t ...

American Physical Society (APS)2025

Electronic Excited States from Physically Constrained Machine Learning

Michele Ceriotti, Jigyasa Nigam, Divya Suman

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

2024

Identification and Quantification of Multiple Drugs by Machine Learning on Electrochemical Sensors for Therapeutic Drug Monitoring

Sandro Carrara, Francesca Rodino, Lin Du

Electrochemical sensors play a pivotal role in advancing therapeutic drug monitoring (TDM) and personalized therapy. However, the insufficient selectivity of electrochemical sensors based on cytochromes P450 poses a great need for innovative machine learni ...

2024

Macroeconomic Conditioned Synthetic Financial Markets

Alexander Michael Rusnak

The creation of high fidelity synthetic data has long been an important goal in machine learning, particularly in fields like finance where the scarcity of available training and test data make it difficult to utilize many of the deep learning techniques w ...

ACM2024

A two-phase approach for leak detection and localization in water distribution systems using wavelet decomposition and machine learning

Jérôme Chenal

Water is a crucial resource for all forms of life, yet it is becoming increasingly scarce. A significant portion of water loss in urban and industrial areas is attributed to leaks. Addressing this issue is critical for enhancing efficiency, sustainability, ...

Elsevier BV2024

A hybrid physics-based and data-driven model for intra-day and day-ahead wind power forecasting considering a drastically expanded predictor search space

Fernando Porté Agel, Nicolas Otto Kirchner Bossi, Gabriel Kathari

This work presents a novel hybrid (physics- and data -driven) model for short-term (intra-day and day-ahead, 3h -24h) wind power forecasting (STWPF). Traditionally, STWPF predictors admitted very few meteorological variables only from the grid points close ...

Elsevier Sci Ltd2024

Learning-based Hand Gesture Classification using Channel Impulse Response with UWB

Clement Weihao Samanos, Han Miao, Andreas Peter Burg, Sitian Li

The channel impulse response (CIR) of the wireless propagation channel is influenced by the surrounding environment and thus can be used to retrieve environmental information such as location, the presence of objects, and the speed of objects. In this work ...

Institute of Electrical and Electronics Engineers Inc.2024

Accelerating Dynamic Aperture Evaluation Using Deep Neural Networks

Tatiana Pieloni, Mike Seidel, Davide Di Croce

The Dynamic Aperture is an important concept for the study of non-linear beam dynamics in a circular accelerator. The DA is defined as the extent of the phase-space region in which the particle's motion remains bounded over a finite number of turns. Such a ...

Institute of Physics2024

Environmental and geographical factors influencing the spread of SARS-CoV-2 over 2 years: a fine-scale spatiotemporal analysis

Stéphane Joost, Anaïs Laurence Ladoy, David Nicolas De Ridder

Introduction Since its emergence in late 2019, the SARS-CoV-2 virus has led to a global health crisis, affecting millions and reshaping societies and economies worldwide. Investigating the determinants of SARS-CoV-2 diffusion and their spatiotemporal dynam ...

FRONTIERS MEDIA SA2024

Acoustic emission signature of martensitic transformation in laser powder bed fusion of Ti6Al4V-Fe, supported by operando X-ray diffraction

Roland Logé, Jamasp Jhabvala, Mathijs Pieter van der Meer, Milad Hamidi Nasab, Reza Esmaeilzadeh, Claire Navarre, Charlotte Léopoldine de Formanoir de la Cazerie, Lucas Maximilian Schlenger

This study focuses on investigating Acoustic Emission (AE) monitoring in the Laser Powder Bed Fusion (LPBF) process, using premixed Ti6Al4V-(x wt%) Fe, where x = 0, 3, and 6. By employing a structure-borne AE sensor, we analyze AE data statistically, uncov ...

2024