Publications related to Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen, Michele Bianco

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

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A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Meta-learning to address diverse Earth observation problems across resolutions

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Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

London2024

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Lausanne2024

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Devis Tuia, Gaston Jean Lenczner, Thiên-Anh Claris Nguyen, Marc Conrad Russwurm

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

Random matrix methods for high-dimensional machine learning models

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In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

A ride time-oriented scheduling algorithm for dial-a-ride problems

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Pergamon-Elsevier Science Ltd2024

Frihet, sikkerhet, forstaden: Brev fra Amerika

Nagy Makhlouf

Why have countries formerly leading public policies of housing – Norway, the U.K., France, etc. – shifted towards privatizing accommodation from the late 1970s? Have these States merely let go of housing and handed it over to private interests in the name ...

2024

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

David Atienza Alonso, José Angel Miranda Calero, Jonathan Dan, Christodoulos Kechris

Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they often un ...

2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

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Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Meta-learning to address diverse Earth observation problems across resolutions

Residual-based attention in physics-informed neural networks

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Random matrix methods for high-dimensional machine learning models

A ride time-oriented scheduling algorithm for dial-a-ride problems

Frihet, sikkerhet, forstaden: Brev fra Amerika

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

A ride time-oriented scheduling algorithm for dial-a-ride problems

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Residual-based attention in physics-informed neural networks

Meta-learning to address diverse Earth observation problems across resolutions

Random matrix methods for high-dimensional machine learning models

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Frihet, sikkerhet, forstaden: Brev fra Amerika