Contrastive Learning Of Structured World Models
Paper : Contrastive Learning Of Structured World Models Code : official 摘要 作者在強化學習任務中，提出了使用GNN來建模多物體之間的關係的方法，使用transE的思路來進行狀態的預測，並通過Contrastive Loss 來進行訓練，提出 C-SWM 模型。作者在雅達利遊戲，多物體物理模擬等任務上達到了SOTA。 方法 C
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相關文章
- 1. A Simple Framework for Contrastive Learning of Visual Representations
- 2. Discriminative Embeddings of Latent Variable Models for Structured Data
- 3. （轉）Applications of Reinforcement Learning in Real World
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- 5. Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow
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- 7. 論文5分鐘 | supervised contrastive learning
- 8. [AAAI2018]Learning Structured Representation Representation for Text Classification via Reinforcemen
- 9. Improved Baselines with Momentum Contrastive Learning
- 10. Representation Learning with Contrastive Predictive Coding