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07/31/2020
Learning the Distribution: A Unified Distillation Paradigm for Fast Uncertainty Estimation in Computer Vision
Calibrated estimates of uncertainty are critical for many real-world com...
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08/27/2018
Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks
Deep learning is known to be data-hungry, which hinders its application ...
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06/08/2017
Gated Orthogonal Recurrent Units: On Learning to Forget
We present a novel recurrent neural network (RNN) based model that combi...
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12/15/2016