Adrien Bibal

34 papers A* 2A 2B 6Journal 16Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
AI Copilots for Reproducibility in Science: A Case Study.
CoRR
Adrien Bibal, Steven N. Minton, Deborah Khider, Yolanda Gil
2025 — conf
Automating Annotation Guideline Improvements using LLMs: A Case Study.
COLING Workshops
Adrien Bibal, Nathaniel Gerlek, Goran Muric, Elizabeth Boschee, Steven Fincke, Mike Ross, Steven N. Minton
2024 J jnl
Granting GPT-4 License and Opportunity: Enhancing Accuracy and Confidence Estimation for Few-Shot Event Detection.
CoRR
Steven Fincke, Adrien Bibal, Elizabeth Boschee
2024 J jnl
RecSOI: recommending research directions using statements of ignorance.
J. Biomed. Semant.
Adrien Bibal, Nourah M. Salem, Rémi Cardon, Elizabeth K. White, Daniel E. Acuna, Robin Burke, Lawrence E. Hunter
2023 — conf
Annotation Linguistique pour l'Évaluation de la Simplification Automatique de Textes.
CORIA-TALN (4)
Rémi Cardon, Adrien Bibal, Rodrigo Wilkens, David Alfter, Magali Norré, Adeline Müller, Patrick Watrin, Thomas François
2023 J jnl
DT-SNE: t-SNE discrete visualizations as decision tree structures.
Neurocomputing
Adrien Bibal, Valentin Delchevalerie, Benoît Frénay
2023 J jnl
Predicting User Preferences of Dimensionality Reduction Embedding Quality.
IEEE Trans. Vis. Comput. Graph.
Cristina Morariu, Adrien Bibal, René Cutura, Benoît Frénay, Michael Sedlmair
2023 J jnl
SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks.
CoRR
Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay
2022 A conf
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence.
CIKM
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
2022 J jnl
Integrating Constraints Into Dimensionality Reduction for Visualization: A Survey.
IEEE Trans. Artif. Intell.
Viet Minh Vu, Adrien Bibal, Benoît Frénay
2022 — conf
Is Attention Explanation? An Introduction to the Debate.
ACL (1)
Adrien Bibal, Rémi Cardon, David Alfter, Rodrigo Wilkens, Xiaoou Wang, Thomas François, Patrick Watrin
2022 — conf
L'Attention est-elle de l'Explication ? Une Introduction au Débat (Is Attention Explanation ? An Introduction to the Debate ).
TALN-RECITAL
Adrien Bibal, Rémi Cardon, David Alfter, Rodrigo Wilkens, Xiaoou Wang, Thomas François, Patrick Watrin
2022 A* conf
Linguistic Corpus Annotation for Automatic Text Simplification Evaluation.
EMNLP
Rémi Cardon, Adrien Bibal, Rodrigo Wilkens, David Alfter, Magali Norré, Adeline Müller, Patrick Watrin, Thomas François
2021 B conf
Accelerating $t$-SNE using Fast Fourier Transforms and the Particle-Mesh Algorithm from Physics.
IJCNN
Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay
2021 A* conf
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks.
NeurIPS
Valentin Delchevalerie, Adrien Bibal, Benoît Frénay, Alexandre Mayer
2021 J jnl
BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation.
Neurocomputing
Adrien Bibal, Rebecca Marion, Rainer von Sachs, Benoît Frénay
2021 J jnl
Constraint Preserving Score for Automatic Hyperparameter Tuning of Dimensionality Reduction Methods for Visualization.
IEEE Trans. Artif. Intell.
Viet Minh Vu, Adrien Bibal, Benoît Frénay
2021 J jnl
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality.
CoRR
Cristina Morariu, Adrien Bibal, René Cutura, Benoît Frénay, Michael Sedlmair
2021 — conf
GanoDIP - GAN Anomaly Detection through Intermediate Patches: a PCBA Manufacturing Case.
LIDTA@ECML/PKDD
Arnaud Bougaham, Adrien Bibal, Isabelle Linden, Benoît Frénay
2021 B conf
HCt-SNE: Hierarchical Constraints with t-SNE.
IJCNN
Viet Minh Vu, Adrien Bibal, Benoît Frénay
2021 J jnl
IXVC: An interactive pipeline for explaining visual clusters in dimensionality reduction visualizations with decision trees.
Array
Adrien Bibal, Antoine Clarinval, Bruno Dumas, Benoît Frénay
2021 J jnl
Legal requirements on explainability in machine learning.
Artif. Intell. Law
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay
2021 — ed.
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
PKDD/ECML Workshops (1)
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 Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 — ed.
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
PKDD/ECML Workshops (2)
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 Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 B conf
iPMDS: Interactive Probabilistic Multidimensional Scaling.
IJCNN
Viet Minh Vu, Adrien Bibal, Benoît Frénay
2020 A conf
AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence.
CIKM
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
2020 B conf
Explaining t-SNE Embeddings Locally by Adapting LIME.
ESANN
Adrien Bibal, Viet Minh Vu, Géraldin Nanfack, Benoît Frénay
2020 J jnl
Impact of Legal Requirements on Explainability in Machine Learning.
CoRR
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay
2020 — —
Interpretability and Explainability in Machine Learning and their Application to Nonlinear Dimensionality Reduction
Adrien Bibal
2019 J jnl
BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables.
Neurocomputing
Rebecca Marion, Adrien Bibal, Benoît Frénay
2018 B conf
Finding the most interpretable MDS rotation for sparse linear models based on external features.
ESANN
Adrien Bibal, Rebecca Marion, Benoît Frénay
2018 J jnl
ML + FV = ♡? A Survey on the Application of Machine Learning to Formal Verification.
CoRR
Moussa Amrani, Levi Lúcio, Adrien Bibal
2016 B conf
Interpretability of machine learning models and representations: an introduction.
ESANN
Adrien Bibal, Benoît Frénay
2016 J jnl
Learning Interpretability for Visualizations using Adapted Cox Models through a User Experiment.
CoRR
Adrien Bibal, Benoît Frénay