Adrien Bibal

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 28

Top Topics

Fourier Transform

Artificial Intelligence

Dimensionality Reduction

Convolutional Neural Networks

Top Venues

Publications

Adrien Bibal, Nourah M. Salem, Rémi Cardon, Elizabeth K. White, Daniel E. Acuna, Robin Burke, Lawrence E. Hunter
RecSOI: recommending research directions using statements of ignorance. J. Biomed. Semant. 15 (1) (2024)
Cristina Morariu, Adrien Bibal, René Cutura, Benoît Frénay, Michael Sedlmair
Predicting User Preferences of Dimensionality Reduction Embedding Quality. IEEE Trans. Vis. Comput. Graph. 29 (1) (2023)
Rémi Cardon, Adrien Bibal, Rodrigo Wilkens, David Alfter, Magali Norré, Adeline Müller, Patrick Watrin, Thomas François
Annotation Linguistique pour l'Évaluation de la Simplification Automatique de Textes. CORIA-TALN (4) (2023)
Adrien Bibal, Valentin Delchevalerie, Benoît Frénay
DT-SNE: t-SNE discrete visualizations as decision tree structures. Neurocomputing 529 (2023)
Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay
SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks. CoRR (2023)
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM (2022)
Adrien Bibal, Rémi Cardon, David Alfter, Rodrigo Wilkens, Xiaoou Wang, Thomas François, Patrick Watrin
Is Attention Explanation? An Introduction to the Debate. ACL (1) (2022)
Rémi Cardon, Adrien Bibal, Rodrigo Wilkens, David Alfter, Magali Norré, Adeline Müller, Patrick Watrin, Thomas François
Linguistic Corpus Annotation for Automatic Text Simplification Evaluation. EMNLP (2022)
Adrien Bibal, Rémi Cardon, David Alfter, Rodrigo Wilkens, Xiaoou Wang, Thomas François, Patrick Watrin
L'Attention est-elle de l'Explication ? Une Introduction au Débat (Is Attention Explanation ? An Introduction to the Debate ). TALN-RECITAL (2022)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
Integrating Constraints Into Dimensionality Reduction for Visualization: A Survey. IEEE Trans. Artif. Intell. 3 (6) (2022)
Arnaud Bougaham, Adrien Bibal, Isabelle Linden, Benoît Frénay
GanoDIP - GAN Anomaly Detection through Intermediate Patches: a PCBA Manufacturing Case. LIDTA@ECML/PKDD (2021)
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay
Legal requirements on explainability in machine learning. Artif. Intell. Law 29 (2) (2021)
Adrien Bibal, Rebecca Marion, Rainer von Sachs, Benoît Frénay
BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation. Neurocomputing 453 (2021)
Adrien Bibal, Antoine Clarinval, Bruno Dumas, Benoît Frénay
IXVC: An interactive pipeline for explaining visual clusters in dimensionality reduction visualizations with decision trees. Array 11 (2021)
Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay
Accelerating $t$-SNE using Fast Fourier Transforms and the Particle-Mesh Algorithm from Physics. IJCNN (2021)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
iPMDS: Interactive Probabilistic Multidimensional Scaling. IJCNN (2021)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
Constraint Preserving Score for Automatic Hyperparameter Tuning of Dimensionality Reduction Methods for Visualization. IEEE Trans. Artif. Intell. 2 (3) (2021)
Cristina Morariu, Adrien Bibal, René Cutura, Benoît Frénay, Michael Sedlmair
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality. CoRR (2021)
Valentin Delchevalerie, Adrien Bibal, Benoît Frénay, Alexandre Mayer
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks. NeurIPS (2021)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
HCt-SNE: Hierarchical Constraints with t-SNE. IJCNN (2021)
Adrien Bibal, Viet Minh Vu, Géraldin Nanfack, Benoît Frénay
Explaining t-SNE Embeddings Locally by Adapting LIME. ESANN (2020)
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay
Impact of Legal Requirements on Explainability in Machine Learning. CoRR (2020)
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM (2020)
Rebecca Marion, Adrien Bibal, Benoît Frénay
BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables. Neurocomputing 342 (2019)
Adrien Bibal, Rebecca Marion, Benoît Frénay
Finding the most interpretable MDS rotation for sparse linear models based on external features. ESANN (2018)
Moussa Amrani, Levi Lúcio, Adrien Bibal
ML + FV = ♡? A Survey on the Application of Machine Learning to Formal Verification. CoRR (2018)
Adrien Bibal, Benoît Frénay
Learning Interpretability for Visualizations using Adapted Cox Models through a User Experiment. CoRR (2016)
Adrien Bibal, Benoît Frénay
Interpretability of machine learning models and representations: an introduction. ESANN (2016)