21 citations · 48 across the 5 of their papers we have counts for
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cs.LG2021★ 4 cited
Challenges and Opportunities in High-dimensional Variational Inference
Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe +3
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 -…
cs.LG2020★ 16 cited
Robust, Accurate Stochastic Optimization for Variational Inference
Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen +3
We consider the problem of fitting variational posterior approximations using stochastic optimization methods. The performance of these approximations depends on (1) how well the v…