1 citations · 2 across the 3 of their papers we have counts for
3 papers
q-bio.PE2026
Linking individual bioenergetics to ecosystem dynamics with integral projection models
Willem Bonnaffé, Martina Muraro, William Goulding +7
Linking individual-level processes, such as survival and reproduction, to ecosystem dynamics is challenging due to interactions among populations and species. These interactions de…
stat.ME2022★ 1 cited
Single chain differential evolution Monte-Carlo for self-tuning Bayesian inference
Willem Bonnaffé
1. Bayesian inference is difficult because it often requires time consuming tuning of samplers. Differential evolution Monte-Carlo (DEMC) is a self-tuning multi-chain sampling appr…
q-bio.PE2022★ 1 cited
Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time series data
Willem Bonnaffé, Tim Coulson
1. Inferring ecological interactions is hard because we often lack suitable parametric representations to portray them. Neural ordinary differential equations (NODEs) provide a way…