Zobrazeno 1 - 10
of 268
pro vyhledávání: '"Verdonck, Tim"'
Robust estimation provides essential tools for analyzing data that contain outliers, ensuring that statistical models remain reliable even in the presence of some anomalous data. While robust methods have long been available in R, users of Python hav
Externí odkaz:
http://arxiv.org/abs/2411.01954
Autor:
Coello, Fernando, Decorte, Thomas, Janssens, Iris, Mortier, Steven, Sardans, Jordi, Peñuelas, Josep, Verdonck, Tim
As global fertilizer application rates increase, high-quality datasets are paramount for comprehensive analyses to support informed decision-making and policy formulation in crucial areas such as food security or climate change. This study aims to fi
Externí odkaz:
http://arxiv.org/abs/2406.10001
Estimating conditional average dose responses (CADR) is an important but challenging problem. Estimators must correctly model the potentially complex relationships between covariates, interventions, doses, and outcomes. In recent years, the machine l
Externí odkaz:
http://arxiv.org/abs/2406.08206
Money laundering presents a pervasive challenge, burdening society by financing illegal activities. To more effectively combat and detect money laundering, the use of network information is increasingly being explored, exploiting that money launderin
Externí odkaz:
http://arxiv.org/abs/2405.19383
Autor:
Mortier, Steven, Hamedpour, Amir, Bussmann, Bart, Wandji, Ruth Phoebe Tchana, Latré, Steven, Sigurdsson, Bjarni D., De Schepper, Tom, Verdonck, Tim
Changes in climate can greatly affect the phenology of plants, which can have important feedback effects, such as altering the carbon cycle. These phenological feedback effects are often induced by a shift in the start or end dates of the growing sea
Externí odkaz:
http://arxiv.org/abs/2312.12258
Accurate forecasts for day-ahead photovoltaic (PV) power generation are crucial to support a high PV penetration rate in the local electricity grid and to assure stability in the grid. We use state-of-the-art tree-based machine learning methods to pr
Externí odkaz:
http://arxiv.org/abs/2312.00090
Autor:
Bockel-Rickermann, Christopher, Vanderschueren, Toon, Berrevoets, Jeroen, Verdonck, Tim, Verbeke, Wouter
Estimating a unit's responses to interventions with an associated dose, the "conditional average dose response" (CADR), is relevant in a variety of domains, from healthcare to business, economics, and beyond. Such a response typically needs to be est
Externí odkaz:
http://arxiv.org/abs/2309.03731
In lending, where prices are specific to both customers and products, having a well-functioning personalized pricing policy in place is essential to effective business making. Typically, such a policy must be derived from observational data, which in
Externí odkaz:
http://arxiv.org/abs/2309.03730
One of the established approaches to causal discovery consists of combining directed acyclic graphs (DAGs) with structural causal models (SCMs) to describe the functional dependencies of effects on their causes. Possible identifiability of SCMs given
Externí odkaz:
http://arxiv.org/abs/2308.05422
Outliers contaminating data sets are a challenge to statistical estimators. Even a small fraction of outlying observations can heavily influence most classical statistical methods. In this paper we propose generalized spherical principal component an
Externí odkaz:
http://arxiv.org/abs/2303.05836