BlackBIRDS: Black-Box Inference foR Differentiable Simulators - Quera-Bofarull, A; Dyer, J; Calinescu, A; Farmer, JD; Wooldridge, M (Open Journal, 2023)
BlackBIRDS is a Python package consisting of generically applicable, black-box inference methods for differentiable simulation models. It facilitates both (a) the differentiable implementation of simulation models by providing a common object-oriented framework for their implementation in PyTorch (Paszke et al., 2019), and (b) the use of a variety of gradient-assisted inference procedures for these simulation models, allowing researchers to easily exploit the differentiable nature of their simulator in parameter estimation tasks. The package consists of both Bayesian and non-Bayesian inference methods, and relies on well-supported software libraries (e.g., normflows, Stimper et al., 2023) to provide this broad functionality.