938 citations
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33 papers · 1 filter
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
Jonghyeon Lee, Boumediene Hamzi, Boya Hou +3
The Koopman operator provides a linear framework to study nonlinear dynamical systems. Its spectra offer valuable insights into system dynamics, but the operator can exhibit both d…
Quantifying the benefit of load uncertainty reduction for the design of district energy systems under grid constraints using the Value of Information
Max Langtry, Ruchi Choudhary
Load uncertainty must be accounted for during design to ensure building energy systems can meet energy demands during operation. Reducing building load uncertainty allows for impro…
Ideology and polarization set the agenda on social media
Edoardo Loru, Alessandro Galeazzi, Anita Bonetti +6
The abundance of information on social media has reshaped public discussions, shifting attention to the mechanisms that drive online discourse. This study analyzes large-scale Twit…
Learning via Surrogate PAC-Bayes
Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj
PAC-Bayes learning is a comprehensive setting for (i) studying the generalisation ability of learning algorithms and (ii) deriving new learning algorithms by optimising a generalis…
AI for Explosive Ordnance Detection in Clearance Operations: The State of Research
Björn Kischelewski, Gregory Cathcart, David Wahl +1
The detection and clearance of explosive ordnance (EO) continues to be a predominantly manual and high-risk process that can benefit from advances in technology to improve its effi…
Causal machine learning for predicting treatment outcomes
Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk +7
Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of…