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06/04/2021
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning
Several families of continual learning techniques have been proposed to ...
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05/19/2021
When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics
Although a plethora of architectural variants for deep classification ha...
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04/14/2021
Neural Architecture Search of Deep Priors: Towards Continual Learning without Catastrophic Interference
In this paper we analyze the classification performance of neural networ...
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09/03/2020
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
Current deep learning research is dominated by benchmark evaluation. A m...
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02/25/2020
Fundamental Issues Regarding Uncertainties in Artificial Neural Networks
Artificial Neural Networks (ANNs) implement a specific form of multi-var...
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08/26/2019
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
We present an analysis of predictive uncertainty based out-of-distributi...
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05/28/2019
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
We introduce a unified probabilistic approach for deep continual learnin...
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12/14/2018
Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures
We characterize convolutional neural networks with respect to the relati...
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05/18/2017
Building effective deep neural network architectures one feature at a time
Successful training of convolutional neural networks is often associated...
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05/31/2016
