Approaches in five categories of CausalML are compared and open problems are identified. Field-specific applications in computer vision, natural language processing and graph representation learning are reviewed. Then, an overview of causal benchmarks and a discussion of the state of this nascent field, with ideas for future work, is provided.
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Approaches in five categories of CausalML are compared and open problems are identified. Field-specific applications in computer vision, natural language processing and graph representation learning are reviewed. Then, an overview of causal benchmarks and a discussion of the state of this nascent field, with ideas for future work, is provided.
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