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Adrien Bibal
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Books and Theses
- 2020
- [b1]Adrien Bibal:
Interpretability and Explainability in Machine Learning and their Application to Nonlinear Dimensionality Reduction. University of Namur, Belgium, 2020
Journal Articles
- 2024
- [j9]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): 2 (2024) - 2023
- [j8]Adrien Bibal
, Valentin Delchevalerie
, Benoît Frénay
:
DT-SNE: t-SNE discrete visualizations as decision tree structures. Neurocomputing 529: 101-112 (2023) - [j7]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): 745-755 (2023) - 2022
- [j6]Viet Minh Vu
, Adrien Bibal
, Benoît Frénay
:
Integrating Constraints Into Dimensionality Reduction for Visualization: A Survey. IEEE Trans. Artif. Intell. 3(6): 944-962 (2022) - 2021
- [j5]Adrien Bibal
, Michael Lognoul
, Alexandre de Streel, Benoît Frénay
:
Legal requirements on explainability in machine learning. Artif. Intell. Law 29(2): 149-169 (2021) - [j4]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: 100080 (2021) - [j3]Adrien Bibal
, Rebecca Marion, Rainer von Sachs, Benoît Frénay
:
BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation. Neurocomputing 453: 109-118 (2021) - [j2]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): 269-282 (2021) - 2019
- [j1]Rebecca Marion
, Adrien Bibal
, Benoît Frénay
:
BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables. Neurocomputing 342: 83-96 (2019)
Conference and Workshop Papers
- 2023
- [c14]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: 35-48 - 2022
- [c13]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: 3889-3900 - [c12]Adrien Bibal
, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
:
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM 2022: 5160 - [c11]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: 1842-1866 - [c10]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: 447-449 - 2021
- [c9]Valentin Delchevalerie
, Alexandre Mayer, Adrien Bibal
, Benoît Frénay
:
Accelerating $t$-SNE using Fast Fourier Transforms and the Particle-Mesh Algorithm from Physics. IJCNN 2021: 1-8 - [c8]Viet Minh Vu, Adrien Bibal
, Benoît Frénay:
iPMDS: Interactive Probabilistic Multidimensional Scaling. IJCNN 2021: 1-8 - [c7]Viet Minh Vu, Adrien Bibal
, Benoît Frénay:
HCt-SNE: Hierarchical Constraints with t-SNE. IJCNN 2021: 1-8 - [c6]Arnaud Bougaham, Adrien Bibal, Isabelle Linden, Benoît Frénay:
GanoDIP - GAN Anomaly Detection through Intermediate Patches: a PCBA Manufacturing Case. LIDTA@ECML/PKDD 2021: 104-117 - [c5]Valentin Delchevalerie, Adrien Bibal, Benoît Frénay, Alexandre Mayer:
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks. NeurIPS 2021: 28772-28783 - 2020
- [c4]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: 3529-3530 - [c3]Adrien Bibal, Viet Minh Vu, Géraldin Nanfack, Benoît Frénay:
Explaining t-SNE Embeddings Locally by Adapting LIME. ESANN 2020: 393-398 - 2018
- [c2]Adrien Bibal, Rebecca Marion, Benoît Frénay:
Finding the most interpretable MDS rotation for sparse linear models based on external features. ESANN 2018 - 2016
- [c1]Adrien Bibal, Benoît Frénay:
Interpretability of machine learning models and representations: an introduction. ESANN 2016
Editorship
- 2021
- [e2]Michael Kamp
, Irena Koprinska
, Adrien Bibal
, Tassadit Bouadi
, Benoît Frénay
, Luis Galárraga
, José Oramas
, Linara Adilova, Yamuna Krishnamurthy
, Bo Kang
, Christine Largeron, Jefrey Lijffijt
, Tiphaine Viard, Pascal Welke
, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele
, Franz Pernkopf
, Michaela Blott
, Holger Fröning
, Günther Schindler, Riccardo Guidotti
, Anna Monreale
, Salvatore Rinzivillo
, Przemyslaw Biecek
, Eirini Ntoutsi
, Mykola Pechenizkiy
, Bodo Rosenhahn
, Christopher L. Buckley
, Daniela Cialfi
, Pablo Lanillos
, Maxwell Ramstead
, Tim Verbelen
, Pedro M. Ferreira
, Giuseppina Andresini
, Donato Malerba
, Ibéria Medeiros
, Philippe Fournier-Viger
, M. Saqib Nawaz
, Sebastián Ventura
, Meng Sun
, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo
, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama
, Ricard Gavaldà
, Lee A. D. Cooper
, Naghmeh Ghazaleh
, Jonas Richiardi
, Damian Roqueiro
, Diego Saldana Miranda
, Konstantinos Sechidis
, Guilherme Graça
:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e1]Michael Kamp
, Irena Koprinska
, Adrien Bibal
, Tassadit Bouadi
, Benoît Frénay
, Luis Galárraga
, José Oramas
, Linara Adilova, Yamuna Krishnamurthy
, Bo Kang
, Christine Largeron, Jefrey Lijffijt
, Tiphaine Viard, Pascal Welke
, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele
, Franz Pernkopf
, Michaela Blott
, Holger Fröning
, Günther Schindler, Riccardo Guidotti
, Anna Monreale
, Salvatore Rinzivillo
, Przemyslaw Biecek
, Eirini Ntoutsi
, Mykola Pechenizkiy
, Bodo Rosenhahn
, Christopher L. Buckley
, Daniela Cialfi
, Pablo Lanillos
, Maxwell Ramstead
, Tim Verbelen
, Pedro M. Ferreira
, Giuseppina Andresini
, Donato Malerba
, Ibéria Medeiros
, Philippe Fournier-Viger
, M. Saqib Nawaz
, Sebastián Ventura
, Meng Sun
, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo
, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama
, Ricard Gavaldà
, Lee A. D. Cooper
, Naghmeh Ghazaleh
, Jonas Richiardi
, Damian Roqueiro
, Diego Saldana Miranda
, Konstantinos Sechidis
, Guilherme Graça
:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents]
Informal and Other Publications
- 2024
- [i6]Steven Fincke, Adrien Bibal, Elizabeth Boschee:
Granting GPT-4 License and Opportunity: Enhancing Accuracy and Confidence Estimation for Few-Shot Event Detection. CoRR abs/2408.00914 (2024) - 2023
- [i5]Valentin Delchevalerie
, Alexandre Mayer, Adrien Bibal, Benoît Frénay:
SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks. CoRR abs/2304.09214 (2023) - 2021
- [i4]Cristina Morariu, Adrien Bibal, René Cutura
, Benoît Frénay, Michael Sedlmair:
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality. CoRR abs/2105.09275 (2021) - 2020
- [i3]Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay:
Impact of Legal Requirements on Explainability in Machine Learning. CoRR abs/2007.05479 (2020) - 2018
- [i2]Moussa Amrani, Levi Lúcio, Adrien Bibal:
ML + FV = ♡? A Survey on the Application of Machine Learning to Formal Verification. CoRR abs/1806.03600 (2018) - 2016
- [i1]Adrien Bibal, Benoît Frénay:
Learning Interpretability for Visualizations using Adapted Cox Models through a User Experiment. CoRR abs/1611.06175 (2016)
Coauthor Index
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last updated on 2024-09-10 23:43 CEST by the dblp team
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