A5058264127- Bayesian Modeling and Causal Inference
- Decision-Making and Behavioral Economics
- Wind Energy Research and Development
- Multi-Criteria Decision Making
- Rough Sets and Fuzzy Logic
- Risk and Portfolio Optimization
- Probabilistic and Robust Engineering Design
- Fuzzy Systems and Optimization
- Formal Methods in Verification
- Computational Physics and Python Applications
- Logic, Reasoning, and Knowledge
- Game Theory and Voting Systems
- Bayesian Methods and Mixture Models
- Advanced Statistical Methods and Models
- Statistical and Computational Modeling
- Advanced Multi-Objective Optimization Algorithms
- Optimization and Mathematical Programming
- Reservoir Engineering and Simulation Methods
- Machine Learning and Data Classification
- Epistemology, Ethics, and Metaphysics
- Data Mining Algorithms and Applications
- Distributed and Parallel Computing Systems
- Semantic Web and Ontologies
- Graph Theory and Algorithms
- Wind and Air Flow Studies
Eindhoven University of Technology
2020-2024
Delft University of Technology
2017-2020
Ghent University
2007-2014
Centrum Wiskunde & Informatica
2014
Carnegie Mellon University
2010-2012
Ghent University Hospital
2003-2010
When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform sensitivity analysis. This can be done by considering as basic uncertainty models so-called credal sets that these known or believed to belong allowing vary over such sets. leads definition an imprecise . We show evolution system studied very efficiently using lower upper expectations , which equivalent mathematical representations also study how inferred set about...
Abstract. Selecting a wind farm layout optimization method is difficult. Comparisons between methods in different papers can be uncertain due to the difficulty of exactly reproducing objective function. by just few authors one paper if do not have experience using each algorithm. In this work we provide an algorithm comparison for case study eight applied, or directed, researchers who developed those algorithms had other them. We provided function researcher avoid ambiguity about relative...
Abstract. Selecting a wind farm layout optimization method is difficult. Comparisons between methods in different papers can be uncertain due to the difficulty of exactly reproducing objective function. by just few authors one paper if do not have experience using each algorithm. In this work we provide an algorithm comparison for case study eight applied, or directed, researchers who developed those algorithms had other them. We provided function researcher avoid ambiguity about relative...
We extend de Finetti's [Ann. Inst. H. Poincaré 7 (1937) 1–68] notion of exchangeability to finite and countable sequences variables, when a subject's beliefs about them are modelled using coherent lower previsions rather than (linear) previsions. derive representation theorems in both the cases, terms sampling without with replacement, respectively.
Abstract. We present an analysis of three datasets 10 min metocean measurement statistics and our resulting recommendations to both producers users such datasets. Many are more generally interest all numerical data producers. The analyzed originate from offshore meteorological masts installed support wind farm planning design: the Dutch OWEZ MMIJ German FINO1. Our shows that contain issues should look out for whose prevalence can be reduced by also expressions derive uncertainty bias values...
Probabilistic models based on continuous latent spaces, such as variational autoencoders, can be understood uncountable mixture where components depend continuously the code. They have proven to expressive tools for generative and probabilistic modelling, but are at odds with tractable inference, that is, computing marginals conditionals of represented probability distribution. Meanwhile, circuits (PCs) hierarchical discrete models, thus capable performing exact inference efficiently often...
Probabilistic circuits are a class of probabilistic generative models that allow us to compute different types queries in polynomial time. Unlike many the mainstream approaches for modeling, they can exact likelihoods, marginals, and expectations. Yet, assessing reliability their inferences is not straightforward. Credal imprecise counterpart allowing, among other queries, computations cautious sensitivity analyses. In this work, we propose an efficient algorithm lower upper expectations...