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VIKING: Deep variational inference with stochastic projections

arXiv — stat.ML•Wednesday, October 29, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
The recent paper titled 'VIKING: Deep variational inference with stochastic projections' addresses the challenges faced by variational mean field approximations in overparametrized deep neural networks. It highlights the common issues of unstable training and poor predictive power, which have hindered the effectiveness of Bayesian methods. By proposing a new variational family based on recent advancements in neural network reparametrizations, this work aims to enhance prediction quality and uncertainty estimation, making it a significant contribution to the field of deep learning.
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