130 citations · 671 across the 42 of their papers we have counts for
44 papers
Fault Trees, Decision Trees, And Binary Decision Diagrams: A Systematic Comparison
L. A. Jimenez-Roa, T. Heskes, M. Stoelinga
In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent…
Deterioration modeling of sewer pipes via discrete-time Markov chains: A large-scale case study in the Netherlands
L. A. Jimenez-Roa, T. Heskes, T. Tinga +2
Sewer pipe network systems are an important part of civil infrastructure, and in order to find a good trade-off between maintenance costs and system performance, reliable sewer pip…
Likelihood-ratio-based confidence intervals for neural networks
Laurens Sluijterman, Eric Cator, Tom Heskes
This paper introduces a first implementation of a novel likelihood-ratio-based approach for constructing confidence intervals for neural networks. Our method, called DeepLR, offers…
Unsupervised anomaly detection algorithms on real-world data: how many do we need?
Roel Bouman, Zaharah Bukhsh, Tom Heskes
In this study we evaluate 32 unsupervised anomaly detection algorithms on 52 real-world multivariate tabular datasets, performing the largest comparison of unsupervised anomaly det…
Optimal Training of Mean Variance Estimation Neural Networks
Laurens Sluijterman, Eric Cator, Tom Heskes
This paper focusses on the optimal implementation of a Mean Variance Estimation network (MVE network) (Nix and Weigend, 1994). This type of network is often used as a building bloc…
Machine Learning Meets The Herbrand Universe
Jelle Piepenbrock, Josef Urban, Konstantin Korovin +3
The appearance of strong CDCL-based propositional (SAT) solvers has greatly advanced several areas of automated reasoning (AR). One of the directions in AR is thus to apply SAT sol…