COURSE

DSAA5037

Introduction to Graph Learning

Information Hub / Data Science and Analytics · 3 Credits

Graph, as a very expressive model, has been widely used to model real-world entities and their relationships in application-specific networks. In this course, students will gain a thorough introduction to the basics of graph theories, as well as cutting-edge research in deep learning for graphs. The topics include graph embeddings, graph neural networks, graph clustering models, graph generative models, adversarial attacks on graphs, graph reasoning, etc.

Course 历年总评分

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难度 · 从难到易

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工作量 · 从劳累到轻松

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评分 · 从苛刻到宽松

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仅展示 2025-26 Spring;历史教学班可通过学期筛选查看。

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官方 Course Catalog

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2025-26 Spring · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26

历史目录与其他学期
2026-27 Fall · PG

3 Credits

官方数据更新时间: 2026-08-28 05:35:00

2025-26 Winter · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26

2025-26 Fall · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26

2024-25 Summer · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26

2024-25 Spring · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26

2024-25 Winter · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26

2024-25 Fall · PG

3 Credits

官方数据更新时间: 2026-08-06 14:55:26