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GT-RIPL

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  1. Evaluate three types of task shifting with popular continual learning algorithms.

    Python 314 66

  2. Learning to Cluster. A deep clustering strategy.

    Python 276 46

  3. PyTorch code for the paper: "FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning"

    Python 32 5

  4. Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"

    Python 24 4

  5. PyTorch code for: Frustratingly Simple Domain Generalization via Image Stylization

    22 2

  6. Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"

    Python 21 4

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