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1		-{{{Virtual Brain Models imply latent nonlinear state space models
2		-driven by noise and network input, necessitating advanced probabilistic
3		-machine learning techniques for widely applicable Bayesian estimation.
4		-Here we present Simulation-based Inference on Virtual Brain Models (SBI-VBMs),
5		-and demonstrate that training deep neural networks on both spatio-temporal and
6		-functional features allows for accurate estimation of generative parameters in brain disorders.
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9		-Code: }}}
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13		-Ref: [[https:~~/~~/iopscience.iop.org/article/10.1088/2632-2153/ad6230>>https://iopscience.iop.org/article/10.1088/2632-2153/ad6230]]
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	29	+{{box title="**Contents**"}}
	30	+{{toc/}}
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