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Found 4 papers, 2 papers with code
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction
In particular, we elaborately devise a Meta-learning Supported Teacher-student GNN (MST-GNN) that is not only built upon teacher-student architecture for alleviating the migration between "easy" and "hard" samples but also equipped with a meta learning based sample re-weighting module for helping the student GNN distinguish "hard" samples in a fine-grained manner.
Learning to Infer Belief Embedded Communication
In multi-agent collaboration problems with communication, an agent's ability to encode their intention and interpret other agents' strategies is critical for planning their future actions.
Open-Ended Multi-Modal Relational Reasoning for Video Question Answering
In this paper, we introduce a robotic agent specifically designed to analyze external environments and address participants' questions.
Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees
We propose a meta path planning algorithm named \emph{Neural Exploration-Exploitation Trees~(NEXT)} for learning from prior experience for solving new path planning problems in high dimensional continuous state and action spaces.
