| Neural ordinary differential equations for ecological and evolutionary time‐series analysis W Bonnaffé, BC Sheldon, T Coulson Methods in Ecology and Evolution 12 (7), 1301-1315, 2021 | 23 | 2021 |
| Species richness and food‐web structure jointly drive community biomass and its temporal stability in fish communities A Danet, M Mouchet, W Bonnaffé, E Thébault, C Fontaine Ecology Letters 24 (11), 2364-2377, 2021 | 18 | 2021 |
| Comparison of size‐structured and species‐level trophic networks reveals antagonistic effects of temperature on vertical trophic diversity at the population and species level W Bonnaffé, A Danet, S Legendre, E Edeline Oikos 130 (8), 1297-1309, 2021 | 12 | 2021 |
| Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time‐series data W Bonnaffé, T Coulson Methods in Ecology and Evolution 14 (6), 1543-1563, 2023 | 8 | 2023 |
| Ontogenetic trajectories of body coloration reveal its function as a multicomponent nonsenescent signal W Bonnaffé, M Martin, M Mugabo, S Meylan, JF Le Galliard Ecology and Evolution 8 (24), 12299-12307, 2018 | 6 | 2018 |
| Inconsistent species interactions across replicated systems may hinder generalisation of dynamical processes W Bonnaffé, T Coulson | | 2024 |
| Beyond attention: deriving biologically interpretable insights from weakly-supervised multiple-instance learning models W Bonnaffé, C Group, F Hamdy, Y Hu, I Mills, J Rittscher, C Verrill, ... arXiv preprint arXiv:2309.03925, 2023 | | 2023 |
| Flexible and Highly-Efficient Feature Perception for Molecular Traits Prediction via Self-interactive Deep Learning Y Hu, K Sirinukunwattana, B Li, K Gaitskell, W Bonnaffe, ... medRxiv, 2023.07. 30.23293391, 2023 | | 2023 |
| Single chain differential evolution Monte-Carlo for self-tuning Bayesian inference W Bonnaffé arXiv preprint arXiv:2209.10252, 2022 | | 2022 |
| Inferring eco-evolutionary feedbacks from time series data using neural ordinary differential equations W Bonnaffe University of Oxford, 2022 | | 2022 |
