Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
Neural Information Processing Systems
Uncertainty estimation aims to evaluate the confidence of a trained deep neural network.
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RDumb: A simple approach that questions our progress in continual test-time adaptation
Ori Press, Steffen Schneider, Matthias Kümmerer, Matthias Bethge
Neural Information Processing Systems
In addition, we introduce a simple baseline, "RDumb", that periodically resets the
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