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A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning

Sep 11, 2020
Martin Mundt, Yong Won Hong, Iuliia Pliushch, Visvanathan Ramesh

* 32 pages 

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Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?

Aug 26, 2019
Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh

* Accepted at the first workshop on Statistical Deep Learning for Computer Vision (SDL-CV) at ICCV 2019 

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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

May 28, 2019
Martin Mundt, Sagnik Majumder, Iuliia Pliushch, Visvanathan Ramesh


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Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset

Apr 02, 2019
Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh

* Accepted for publication at CVPR 2019. Version includes supplementary material 

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Rethinking Layer-wise Feature Amounts in Convolutional Neural Network Architectures

Dec 14, 2018
Martin Mundt, Sagnik Majumder, Tobias Weis, Visvanathan Ramesh

* Accepted at the Critiquing and Correcting Trends in Machine Learning (CRACT) Workshop at the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018) 

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Building effective deep neural network architectures one feature at a time

Oct 19, 2017
Martin Mundt, Tobias Weis, Kishore Konda, Visvanathan Ramesh


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