Publications associées à A dynamic discrete-continuous choice model for forward-looking agents owning one or more vehicles

How Words Move Hearts: Interpretable Machine Learning Models of Bias, Engagement, and Influence in Socio-Political Systems

We study socio-political systems in representative democracies. Motivated by problems that affect the proper functioning of the system, we build computational methods to answer research questions regarding the phenomena occurring in them. For each phenomen ...

EPFL2023

Systematic extraction of a control-oriented model from perturbative experiments and SOLPS-ITER for emission front control in TCV

Artur Perek, Olivier Claude Martin Février, Mirko Wensing

Systematic extraction of locally valid dynamic models from experiments is necessary for controller design and the validation of high fidelity models. This paper describes the extraction of a dynamic model in the form of a transfer function, giving the dyna ...

IOP Publishing Ltd2022

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Daniel Keller

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate a specific hypothesis about how the system work ...

2022

Wind-Topo_Model

Michael Lehning, Jérôme François Sylvain Dujardin

Model and Data: Dujardin, J.; Lehning, M. Wind-Topo_model. EnviDat 2022 ...

Zenodo2022

Tree root distribution modelling in different environmental conditions

David Andrew Barry, Paolo Perona, Massimiliano Schwarz

The ability to predict the spatial distribution of tree root system variables (e.g., the Root system Area (RA), the maximum root diameter, the number of roots in diameter classes, the density of fine roots, etc.) under different environmental conditions is ...

2022

Non-intrusive double-greedy parametric model reduction by interpolation of frequency-domain rational surrogates

Fabio Nobile, Davide Pradovera

We propose a model order reduction approach for non-intrusive surrogate modeling of parametric dynamical systems. The reduced model over the whole parameter space is built by combining surrogates in frequency only, built at few selected values of the param ...

2021

Product of experts for robot learning from demonstration

Emmanuel Pignat

Adaptability and ease of programming are key features necessary for a wider spread of robotics in factories and everyday assistance. Learning from demonstration (LfD) is an approach to address this problem. It aims to develop algorithms and interfaces such ...

EPFL2021

Exploring policy change through agent-based simulation

Raphaël Klein

Policymaking is a complex process that has been studied using policy process theories almost exclusively. These theories have been built using a large number of qualitative cases. Such methods are useful for theory building but remain limited for theory ex ...

EPFL2021

Distributionally Robust Optimization with Markovian Data

Daniel Kuhn, Tobias Sutter, Mengmeng Li

We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

Jan Sickmann Hesthaven, Caterina Bigoni

We propose a simulation-based decision strategy for the proactive maintenance of complex structures with a particular application to structural health monitoring (SHM). The strategy is based on a data-driven approach which exploits an offline-online decomp ...

2020