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Causal machine learning for predicting treatment outcomes
Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of drugs. A key benefit of caus...
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Chapter and Conference Paper
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned
In this work, we focus on the problem of entity alignment in Knowledge Graphs (KG) and we report on our experiences when applying a Graph Convolutional Network (GCN) based model for this task. Variants of GCN ...
