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Found 4 papers, 2 papers with code
Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning
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)
Self Paced Adversarial Training for Multimodal Few-shot Learning
State-of-the-art deep learning algorithms yield remarkable results in many visual recognition tasks.
Cross-modal Hallucination for Few-shot Fine-grained Recognition
State-of-the-art deep learning algorithms generally require large amounts of data for model training.
Scalable Generalized Dynamic Topic Models
First, we extend the class of tractable priors from Wiener processes to the generic class of Gaussian processes (GPs).
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