TimeSAE: Sparse Decoding for Faithful Explanations of Black-Box Time Series Models
Khalid Oublal, Quentin Bouniot, Qi Gan, Stephan Clémençon, Zeynep Akata
International Conference on Machine Learning (ICML), 2026
Publications
You can also find my articles on my Google Scholar profile.
SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport
Simon Roschmann, Paul Krzakala, Sonia Mazelet, Quentin Bouniot, Zeynep Akata
International Conference on Machine Learning (ICML), 2026
Dissecting Multimodal In-Context Learning: Modality Asymmetries and Circuit Dynamics in modern Transformers
Yiran Huang, Karsten Roth, Quentin Bouniot, Wenjia Xu, Zeynep Akata
International Conference on Machine Learning (ICML), 2026
Mantis: Lightweight Foundation Model for Time Series Classification
Vasilii Feofanov, Songkang Wen, Shifeng Xie, Simon Roschmann, Marius Alonso, Hongbo Guo, Romain Ilbert, Malik Tiomoko, Quentin Bouniot, Zeynep Akata, Lujia Pan, Jianfeng Zhang, Ievgen Redko
International Conference on Machine Learning (ICML), 2026
The Latent Color Subspace: Emergent Order in High-Dimensional Chaos
Mateusz Pach, Jessica Bader, Quentin Bouniot, Serge Belongie, Zeynep Akata
International Conference on Machine Learning (ICML), 2026
Rethinking Concept Bottleneck Models: From Pitfalls to Solutions
Merve Tapli, Quentin Bouniot, Wolfgang Stammer, Zeynep Akata, Emre Akbas
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2026
Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models
Mateusz Pach, Shyamgopal Karthik, Quentin Bouniot, Serge Belongie, Zeynep Akata
Neural Information Processing Systems (NeurIPS), 2025
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
Quentin Bouniot*, Ievgen Redko*, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Permalink
Jayneel Parekh*, Quentin Bouniot*, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc
International Conference on Learning Representations (ICLR), 2025
Tailoring Mixup to Data for Calibration
Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc
International Conference on Learning Representations (ICLR), 2025
Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks
Quentin Bouniot
PhD Thesis, 2023
Proposal-Contrastive Pretraining for Object Detection from Fewer Data
Quentin Bouniot, Romaric Audigier, Angelique Loesch, Amaury Habrard
International Conference on Learning Representations (ICLR), 2023
Towards Few-Annotation Learning for Object Detection: Are Transformer-Based Models More Efficient?
Quentin Bouniot, Angélique Loesch, Romaric Audigier, Amaury Habrard
IEEE Winter Conference on Applications of Computer Vision (WACV), 2023
Improving Few-Shot Learning through Multi-task Representation Learning Theory
Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard
European Conference on Computer Vision (ECCV), 2022
Optimal Transport as a Defense Against Adversarial Attacks
Quentin Bouniot, Romaric Audigier, Angélique Loesch
IEEE International Conference on Pattern Recognition (ICPR), 2021
Vulnerability of Person Re-Identification Models to Metric Adversarial Attacks.
Quentin Bouniot, Romaric Audigier, Angélique Loesch
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop, 2020