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09/08/2023
UER: A Heuristic Bias Addressing Approach for Online Continual Learning
Online continual learning aims to continuously train neural networks fro...
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07/31/2023
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
Equipping a deep model the abaility of few-shot learning, i.e., learning...
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04/10/2023
PCR: Proxy-based Contrastive Replay for Online Class-Incremental Continual Learning
Online class-incremental continual learning is a specific task of contin...
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03/03/2022
MetaDT: Meta Decision Tree for Interpretable Few-Shot Learning
Few-Shot Learning (FSL) is a challenging task, which aims to recognize n...
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10/09/2021
SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification
Few-Shot Remote Sensing Scene Classification (FSRSSC) is an important ta...
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08/11/2021
Prototype Completion for Few-Shot Learning
Few-shot learning aims to recognize novel classes with few examples. Pre...
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03/26/2021
MetaNODE: Prototype Optimization as a Neural ODE for Few-Shot Learning
Few-Shot Learning (FSL) is a challenging task, i.e., how to recognize no...
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09/10/2020
Prototype Completion with Primitive Knowledge for Few-Shot Learning
Few-shot learning is a challenging task, which aims to learn a classifie...
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07/05/2020
