| A deep learning approach to self-expansion of abbreviations based on morphology and context distance D Chopard, I Spasić Statistical Language and Speech Processing: 7th International Conference …, 2019 | 9 | 2019 |
| Text Mining of Adverse Events in Clinical Trials: Deep Learning Approach D Chopard, MS Treder, P Corcoran, N Ahmed, C Johnson, M Busse, ... JMIR Medical Informatics 9 (12), e28632, 2021 | 6 | 2021 |
| Simulation and annotation of global acronyms M Filimonov, D Chopard, I Spasić Bioinformatics 38 (11), 3136-3138, 2022 | 3 | 2022 |
| Learning Data Augmentation Schedules for Natural Language Processing D Chopard, MS Treder, I Spasić Proceedings of the Second Workshop on Insights from Negative Results in NLP …, 2021 | 3 | 2021 |
| Unity by Diversity: Improved Representation Learning in Multimodal VAEs TM Sutter, Y Meng, N Fortin, JE Vogt, S Mandt arXiv preprint arXiv:2403.05300, 2024 | 1 | 2024 |
| Word sense disambiguation of acronyms in clinical narratives D Chopard, P Corcoran, I Spasić Frontiers in Digital Health 6, 1282043, 2024 | | 2024 |
| Comparison of carbon dioxide control during pressure controlled versus pressure regulated volume controlled ventilation in children (CoCO2): protocol for a pilot digital … R Mozun, D Chopard, F Zapf, P Baumann, B Brotschi, A Adam, V Jaegi, ... medRxiv, 2024.03. 29.24305023, 2024 | | 2024 |
| Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders E Palumbo, L Manduchi, S Laguna, D Chopard, JE Vogt The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
| Deep Generative Clustering with Multimodal Variational Autoencoders E Palumbo, S Laguna, D Chopard, JE Vogt | | 2023 |
| Deep learning for clinical texts in low-data regimes D Chopard Cardiff University, 2023 | | 2023 |
