no code implementations • 17 Nov 2020 • Frederik Pahde, Mihai Puscas, Tassilo Klein, Moin Nabi
Although providing exceptional results for many computer vision tasks, state-of-the-art deep learning algorithms catastrophically struggle in low data scenarios.
no code implementations • ICLR 2019 • Oleksiy Ostapenko, Mihai Puscas, Tassilo Klein, Moin Nabi
Continuously trainable models should be able to learn from a stream of data over an undefined period of time.
2 code implementations • CVPR 2019 • Oleksiy Ostapenko, Mihai Puscas, Tassilo Klein, Patrick Jähnichen, Moin Nabi
In order to tackle these challenges, we introduce Dynamic Generative Memory (DGM) - a synaptic plasticity driven framework for continual learning.
Ranked #4 on Continual Learning on ImageNet-50 (5 tasks)
no code implementations • 4 Jan 2019 • Frederik Pahde, Mihai Puscas, Jannik Wolff, Tassilo Klein, Nicu Sebe, Moin Nabi
Since the advent of deep learning, neural networks have demonstrated remarkable results in many visual recognition tasks, constantly pushing the limits.