56 citations · 83 across the 11 of their papers we have counts for
11 papers
Data-Efficient Interactive Multi-Objective Optimization Using ParEGO
Arash Heidari, Sebastian Rojas Gonzalez, Tom Dhaene +1
Multi-objective optimization is a widely studied problem in diverse fields, such as engineering and finance, that seeks to identify a set of non-dominated solutions that provide op…
ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization
Jixiang Qing, Henry B. Moss, Tom Dhaene +1
We present Parallel Feasible Pareto Frontier Entropy Search (ES) -- a novel information-theoretic acquisition function for multi-objective Bayesian optimization su…
A Robust Multi-Objective Bayesian Optimization Framework Considering Input Uncertainty
J. Qing, I. Couckuyt, T. Dhaene
Bayesian optimization is a popular tool for data-efficient optimization of expensive objective functions. In real-life applications like engineering design, the designer often want…
Sensor Fusion using Backward Shortcut Connections for Sleep Apnea Detection in Multi-Modal Data
Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene
Sleep apnea is a common respiratory disorder characterized by breathing pauses during the night. Consequences of untreated sleep apnea can be severe. Still, many people remain undi…
Generating an Explainable ECG Beat Space With Variational Auto-Encoders
Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene
Electrocardiogram signals are omnipresent in medicine. A vital aspect in the analysis of this data is the identification and classification of heart beat types which is often done…
GPflowOpt: A Bayesian Optimization Library using TensorFlow
Nicolas Knudde, Joachim van der Herten, Tom Dhaene +1
A novel Python framework for Bayesian optimization known as GPflowOpt is introduced. The package is based on the popular GPflow library for Gaussian processes, leveraging the benef…