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03/02/2023
Deep Neural Networks with Efficient Guaranteed Invariances
We address the problem of improving the performance and in particular th...
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05/17/2022
Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep Neural Network, a Survey
State-of-the-art deep learning models have a parameter count that reache...
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03/15/2022
Interspace Pruning: Using Adaptive Filter Representations to Improve Training of Sparse CNNs
Unstructured pruning is well suited to reduce the memory footprint of co...
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02/08/2022
Improving the Sample-Complexity of Deep Classification Networks with Invariant Integration
Leveraging prior knowledge on intraclass variance due to transformations...
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08/21/2020
A Survey on Assessing the Generalization Envelope of Deep Neural Networks at Inference Time for Image Classification
Deep Neural Networks (DNNs) achieve state-of-the-art performance on nume...
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06/30/2020
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey
While Deep Neural Networks (DNNs) achieve state-of-the-art results in ma...
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04/20/2020
GraN: An Efficient Gradient-Norm Based Detector for Adversarial and Misclassified Examples
Deep neural networks (DNNs) are vulnerable to adversarial examples and o...
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04/20/2020
