| Data augmentation in high dimensional low sample size setting using a geometry-based variational autoencoder C Chadebec, E Thibeau-Sutre, N Burgos, S Allassonnière IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 2879-2896, 2022 | 69 | 2022 |
| Pythae: Unifying Generative Autoencoders in Python--A Benchmarking Use Case C Chadebec, LJ Vincent, S Allassonnière Advances in Neural Information Processing Systems 35, 2022 | 29 | 2022 |
| Data Augmentation with Variational Autoencoders and Manifold Sampling C Chadebec, S Allassonnière Deep Generative Models, and Data Augmentation, Labelling, and Imperfections …, 2021 | 22* | 2021 |
| A Geometric Perspective on Variational Autoencoders C Chadebec, S Allassonnière Advances in Neural Information Processing Systems 35, 2022 | 16 | 2022 |
| Geometry-aware hamiltonian variational auto-encoder C Chadebec, C Mantoux, S Allassonnière arXiv preprint arXiv:2010.11518, 2020 | 15 | 2020 |
| Improving Multimodal Joint Variational Autoencoders through Normalizing Flows and Correlation Analysis A Senellart, C Chadebec, S Allassonnière arXiv preprint arXiv:2305.11832, 2023 | 2 | 2023 |
| MultiVae: A Python library for Multimodal Generative Autoencoders A Senellart, C Chadebec, S Allassonnière | 1 | 2023 |
| Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation C Chadebec, O Tasar, E Benaroche, B Aubin arXiv preprint arXiv:2406.02347, 2024 | | 2024 |
| Modeling the Latent Space of Variational Autoencoders C Chadebec Université Paris Cite, 2023 | | 2023 |
| Variational Inference for Longitudinal Data Using Normalizing Flows C Chadebec, S Allassonnière arXiv preprint arXiv:2303.14220, 2023 | | 2023 |
| An Image Feature Mapping Model for Continuous Longitudinal Data Completion and Generation of Synthetic Patient Trajectories C Chadebec, EMC Huijben, JPW Pluim, S Allassonnière, ... MICCAI Workshop on Deep Generative Models, 55-64, 2022 | | 2022 |
