BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables R Marion, A Bibal, B Frénay Neurocomputing 342, 83-96, 2019 | 17 | 2019 |
The essentials on linear regression, ANOVA, general linear and linear mixed models for the chemist B Govaerts, B Francq, R Marion, M Martin, M Thiel Reference Module in Chemistry, Molecular Sciences and Chemical Engineering 2, 2020 | 13 | 2020 |
Finding the most interpretable MDS rotation for sparse linear models based on external features A Bibal, R Marion, B Frénay 26th European Symposium on Artificial Neural Networks, Computational …, 2018 | 11 | 2018 |
BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation A Bibal, R Marion, R von Sachs, B Frénay Neurocomputing 453, 109-118, 2021 | 9 | 2021 |
AdaCLV for interpretable variable clustering and dimensionality reduction of spectroscopic data R Marion, B Govaerts, R von Sachs Chemometrics and Intelligent Laboratory Systems 206, 104169, 2020 | 4 | 2020 |
Comparison of Cluster Validity Indices and Decision Rules for Different Degrees of Cluster Separation S Kaczynska, R Marion, R von Sachs ESANN, 2020 | 3 | 2020 |
Globally local and fast explanations of t-SNE-like nonlinear embeddings P Lambert, R Marion, J Albert, E Jean, S Corbugy, C de Bodt 2022 International Conference on Information and Knowledge Management …, 2022 | 2 | 2022 |
VC-PCR: A Prediction Method based on Supervised Variable Selection and Clustering R Marion, J Lederer, B Govaerts, R von Sachs arXiv preprint arXiv:2202.00975, 2022 | 1 | 2022 |
Pre-processing of nmr spectra: review and evaluation of baseline correction, normalization, scaling and transformation methods R Marion | 1 | 2016 |
Gradient-based explanation for non-linear non-parametric dimensionality reduction S Corbugy, R Marion, B Frénay Data Mining and Knowledge Discovery, 1-29, 2024 | | 2024 |
Improving the Feature Selection Stability of the Delta Test in Regression R Marion, B Frénay IEEE Transactions on Artificial Intelligence, 2023 | | 2023 |
Globally local and fast explanations of 𝑡-SNE-like nonlinear embeddings P Lambert, R Marion, J Albert, E Jean, S Corbugy, C de Bodt | | 2022 |
Statistical and Machine Learning Methods for Identifying Clusters of Variables R Marion Université catholique de Louvain, 2021 | | 2021 |