论文标题
分子图的体现符号对比图自制学习
Embodied-Symbolic Contrastive Graph Self-Supervised Learning for Molecular Graphs
论文作者
论文摘要
双重体现符号概念表示是深度学习和符号AI整合的基础。我们讨论了双重体现符号概念表示在分子图表示学习中的使用，特别是基于示例性的对比度自学学习（SSL）。从分子图中学到了体现的表示，并从相应的化学知识图（kg）中学到符号表示。我们使用化学kg来增强具有符号（语义）知识的分子图，并生成它们增强的分子图。我们将分子图及其语义增强的分子图视为同一语义类别的示例，并将对作为基于示例的对比度SSL中的正对作为正面。
Dual embodied-symbolic concept representations are the foundation for deep learning and symbolic AI integration. We discuss the use of dual embodied-symbolic concept representations for molecular graph representation learning, specifically with exemplar-based contrastive self-supervised learning (SSL). The embodied representations are learned from molecular graphs, and the symbolic representations are learned from the corresponding Chemical knowledge graph (KG). We use the Chemical KG to enhance molecular graphs with symbolic (semantic) knowledge and generate their augmented molecular graphs. We treat a molecular graph and its semantically augmented molecular graph as exemplars of the same semantic class, and use the pairs as positive pairs in exemplar-based contrastive SSL.
