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.


Quera-Bofarull, A., Dyer, J., Calinescu, A., Farmer, J.D. & Wooldridge, M.(2023). BlackBIRDS: Black-Box Inference for Differentiable Simulators. Journal of Open Source Software, 8(89), 5776. https://doi.org/10.21105/joss.05776.
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