Learning from the Past: Continaul Meta-Learning with Bayesian Graph Neural network review
1. 提出問題 現有的基於圖網絡做meta-learning的方法會有Catastrophic forgetting 和 insufficient robustness的問題， 導致不嗯呢個保持long-term的knowledge，並會造成嚴重的錯誤積累。 Catastraphic forgetting insufficient robustness 2. 提出解決方案 針對Catastraph
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相關文章
- 1. Review on The Graph Neural Network Model
- 2. Graph Neural Network Review
- 3. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORK
- 4. Few-Shot Learning with Graph Neural Networks
- 5. Learning about Graph Network
- 6. 3 The Bayesian Network Representation
- 7. Few-shot Learning with Graph Neural Networks
- 8. 《The graph neural network model》筆記
- 9. Fast deep reinforcement learning using online adjustments from the past
- 10. 【KDD 2019】Heterogeneous Graph Neural Network