Wang-ML-Lab/GRDA
[ICLR 2022] Graph-Relational Domain Adaptation
When you have data from multiple similar, but distinct, sources (like different geographic regions, product lines, or sensor types) and need to apply insights learned from one set of sources to others, this project helps. It takes data from several related "domains" and a "domain graph" showing how these domains are connected (e.g., states sharing a border). It then produces a model that can generalize across all connected domains. This is ideal for researchers or data scientists working with diverse, interconnected datasets.
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Use this if you need to build a machine learning model that performs well across multiple related data domains, where the relationships between these domains can be described as a graph.
Not ideal if your different data sources are completely unrelated or if you only need to adapt knowledge between two distinct domains without considering a network of relationships.
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Language
Python
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Last pushed
Apr 12, 2024
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