arXiv cs.LG
· Papers
Divide-and-Conquer: Towards Generalizable Amortized Bayesian Inference for the Drift Diffusion Model
arXiv:2608.03566v1 Announce Type: cross Abstract: The drift diffusion model (DDM) is a cornerstone of cognitive decision-making research. Although numerous estimation methods exist, researchers continue to seek inference approaches that are both fast and flexible across diverse study designs. Amortized Bayesian inferen