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Incorporating Projective Geometry into Deep Learning
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Enabling Uncertainty Estimation in Iterative Neural Networks
Pascal Fua, Nikita Durasov, Doruk Oner, Minh Hieu Lê
Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...
Curran Associates2024