2 citations · 2 across the 2 of their papers we have counts for
3 papers
Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
Jonas Arruda, Sophie Chervet, Paula Staudt +6
Selection bias arises when the probability that an observation enters a dataset depends on variables related to the quantities of interest, leading to systematic distortions in est…
BayesFlow 2: Multi-Backend Amortized Bayesian Inference in Python
Lars Kühmichel, Jerry M. Huang, Valentin Pratz +11
Modern Bayesian inference involves a mixture of computational methods for estimating, validating, and drawing conclusions from probabilistic models as part of principled workflows.…
Compositional amortized inference for large-scale hierarchical Bayesian models
Jonas Arruda, Vikas Pandey, Catherine Sherry +4
Amortized Bayesian inference (ABI) with neural networks has emerged as a powerful simulation-based approach for estimating complex mechanistic models. However, extending ABI to hie…