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  • title: Challenges and Opportunities in High-dimensional Variational Inference
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            Challenges and Opportunities in High-dimensional Variational Inference
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            Challenges and Opportunities in High-dimensional Variational Inference

            Dec 6, 2021

            Speakers

            AKD

            Akash Kumar Dhaka

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            AC

            Alejandro Catalina

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            MW

            Manushi Welandawe

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            About

            Current black-box variational inference (BBVI) methods require the user to make numerous design choices – such as the selection of variational objective and approximating family – yet there is little principled guidance on how to do so. We develop a conceptual framework and set of experimental tools to understand the effects of these choices, which we leverage to propose best practices for maximizing posterior approximation accuracy. Our approach is based on studying the pre-asymptotic tail beha…

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            NeurIPS 2021

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