38 citations
- Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et EnergétiqueFR4 papers
- Université de LilleFR3 papers
- Université Paris-SaclayFR3 papers
- University College LondonGB3 papers
- Centre BorelliFR2 papers
- Centre Inria de l'Université de LilleFR2 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Laboratoire de Physique des PlasmasFR2 papers
- Laboratoire Interdisciplinaire des Sciences du NumériqueFR2 papers
- Laboratoire Paul PainlevéFR2 papers
- Local Initiatives Support CorporationUS2 papers
- University of LondonGB2 papers
10 papers
AK-MCS-C2 : Active Kriging Monte Carlo Simulation method with conformal certification for failure probability estimation
Edgar Jaber, Vincent Chabridon, Mathilde Mougeot
We introduce a novel active-learning framework for failure probability estimation in structural reliability analysis that integrates Active Kriging Monte Carlo simulation with conf…
Fourier Analysis on the Boolean Hypercube via Hoeffding Functional Decomposition
Baptiste Ferrere, Nicolas Bousquet, Fabrice Gamboa +2
Fourier analysis on the Boolean hypercube is fundamentally defined as the orthogonal decomposition of the space of pseudo-Boolean functions with respect to the uniform probability…
Fusion of heterogeneous data for robust degradation prognostics
Edgar Jaber, Emmanuel Remy, Vincent Chabridon +2
Assessing the degradation state of an industrial asset first requires evaluating its current condition and then to project the forecast model trajectory to a predefined prognostic…
Phase-resolved Modeling Of Surf Zone Wave Transformation Over Idealized Rough Bottoms
Emile Guélard-Ancilotti, Damien Sous, Denis Morichon +3
Rough rocky seabeds dominate world's coastlines, making accurate modeling of wave transformation in such environments essential for understanding coastal processes and hazards. Wav…
How good is PAC-Bayes at explaining generalisation?
Antoine Picard-Weibel, Eugenio Clerico, Roman Moscoviz +1
We discuss necessary conditions for a PAC-Bayes bound to provide a meaningful generalisation guarantee. Our analysis reveals that the optimal generalisation guarantee depends solel…
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…