17 citations · 25 across the 4 of their papers we have counts for
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cs.LG2020
Uncertainty in Neural Processes
Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy +1
We explore the effects of architecture and training objective choice on amortized posterior predictive inference in probabilistic conditional generative models. We aim this work to…
cs.LG2020★ 17 cited
On the Benefits of Invariance in Neural Networks
Clare Lyle, Mark van der Wilk, Marta Kwiatkowska +2
Many real world data analysis problems exhibit invariant structure, and models that take advantage of this structure have shown impressive empirical performance, particularly in de…