10 citations · 18 across the 7 of their papers we have counts for
7 papers
Autoencoders for Anomaly Detection are Unreliable
Roel Bouman, Tom Heskes
Autoencoders are frequently used for anomaly detection, both in the unsupervised and semi-supervised settings. They rely on the assumption that when trained using the reconstructio…
Comparing Homogeneous And Inhomogeneous Time Markov Chains For Modelling Degradation In Sewer Pipe Networks
Lisandro A. Jimenez-Roa, Tiedo Tinga, Tom Heskes +1
Sewer pipe systems are essential for social and economic welfare. Managing these systems requires robust predictive models for degradation behaviour. This study focuses on probabil…
Composite Quantile Regression With XGBoost Using the Novel Arctan Pinball Loss
Laurens Sluijterman, Frank Kreuwel, Eric Cator +1
This paper explores the use of XGBoost for composite quantile regression. XGBoost is a highly popular model renowned for its flexibility, efficiency, and capability to deal with mi…
Acquiring Better Load Estimates by Combining Anomaly and Change Point Detection in Power Grid Time-series Measurements
Roel Bouman, Linda Schmeitz, Luco Buise +3
In this paper we present novel methodology for automatic anomaly and switch event filtering to improve load estimation in power grid systems. By leveraging unsupervised methods wit…
Pfeed: Generating near real-time personalized feeds using precomputed embedding similarities
Binyam Gebre, Karoliina Ranta, Stef van den Elzen +3
In personalized recommender systems, embeddings are often used to encode customer actions and items, and retrieval is then performed in the embedding space using approximate neares…
Tuning neural posterior estimation for gravitational wave inference
Alex Kolmus, Justin Janquart, Tomasz Baka +3
Modern simulation-based inference techniques use neural networks to solve inverse problems efficiently. One notable strategy is neural posterior estimation (NPE), wherein a neural…
Bayesian Inference of Whole-Brain Networks
M. Hinne, T. Heskes, M. A. J. van Gerven
In structural brain networks the connections of interest consist of white-matter fibre bundles between spatially segregated brain regions. The presence, location and orientation of…