This map shows the geographic impact of Adrien Bibal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Adrien Bibal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrien Bibal more than expected).
This network shows the impact of papers produced by Adrien Bibal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Adrien Bibal. The network helps show where Adrien Bibal may publish in the future.
Co-authorship network of co-authors of Adrien Bibal
This figure shows the co-authorship network connecting the top 25 collaborators of Adrien Bibal.
A scholar is included among the top collaborators of Adrien Bibal based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Adrien Bibal. Adrien Bibal is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bibal, Adrien, et al.. (2022). Is Attention Explanation? An Introduction to the Debate. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 3889–3900.31 indexed citations
Bibal, Adrien, et al.. (2021). Achieving Rotational Invariance with Bessel-Convolutional Neural Networks. Repository of the University of Namur. 34.5 indexed citations
Bibal, Adrien, et al.. (2021). GanoDIP - GAN Anomaly Detection through Intermediate Patches: a PCBA Manufacturing Case. Repository of the University of Namur.4 indexed citations
13.
Bibal, Adrien, et al.. (2020). Explaining t-SNE Embeddings Locally by Adapting LIME.. Repository of the University of Namur. 393–398.2 indexed citations
Bibal, Adrien, Bruno Dumas, & Benoît Frénay. (2019). User-Based Experiment Guidelines for Measuring Interpretability in Machine Learning. Repository of the University of Namur.1 indexed citations
Bibal, Adrien, et al.. (2018). Finding the most interpretable MDS rotation for sparse linear models based on external features.. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)).7 indexed citations
18.
Levi, Lucio, et al.. (2018). ML + FV = ♡? A Survey on the Application of Machine Learning to Formal Verification..4 indexed citations
19.
Bibal, Adrien & Benoît Frénay. (2016). Interpretability of machine learning models and representations: an introduction.. Repository of the University of Namur.54 indexed citations
20.
Combéfis, Sébastien, Adrien Bibal, & Peter Van Roy. (2014). Recasting a traditional course into a MOOC by means of a SPOC. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 205–208.17 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.