5 citations · 7 across the 3 of their papers we have counts for
8 papers
GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data
Ana Kostovska, Matej Petković, Tomaž Stepišnik +8
We present GalaxAI - a versatile machine learning toolbox for efficient and interpretable end-to-end analysis of spacecraft telemetry data. GalaxAI employs various machine learning…
Discovering outliers in the Mars Express thermal power consumption patterns
Matej Petković, Luke Lucas, Tomaž Stepišnik +3
The Mars Express (MEX) spacecraft has been orbiting Mars since 2004. The operators need to constantly monitor its behavior and handle sporadic deviations (outliers) from the expect…
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings
Blaž Škrlj, Sašo Džeroski, Nada Lavrač +1
Feature ranking has been widely adopted in machine learning applications such as high-throughput biology and social sciences. The approaches of the popular Relief family of algorit…
Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning
Matej Petković, Dragi Kocev, Blaž Škrlj +1
In this work, we propose two novel (groups of) methods for unsupervised feature ranking and selection. The first group includes feature ranking scores (Genie3 score, RandomForest s…
Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots
Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras +20
The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed usin…
Feature Ranking for Semi-supervised Learning
Matej Petković, Sašo Džeroski, Dragi Kocev
The data made available for analysis are becoming more and more complex along several directions: high dimensionality, number of examples and the amount of labels per example. This…