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Found 5 papers, 2 papers with code
Flatness Improves Backbone Generalisation in Few-shot Classification
Deployment of deep neural networks in real-world settings typically requires adaptation to new tasks with few examples.
Learn the Time to Learn: Replay Scheduling in Continual Learning
In such settings, we propose that continual learning systems should learn the time to learn and schedule which tasks to replay at different time steps.
Learn the Time to Learn: Replay Scheduling for Continual Learning
Inspired by human learning, we illustrate that scheduling over which tasks to revisit is critical to the final performance with finite memory resources.
A Hierarchical Grocery Store Image Dataset with Visual and Semantic Labels
In this paper, we provide a new benchmark dataset for a challenging task in this application - classification of fruits, vegetables, and refrigerated products, e. g. milk packages and juice cartons, in grocery stores.
Causality Refined Diagnostic Prediction
In this work, we explore the possibility of utilizing causal relationships to refine diagnostic prediction.
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