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Found 3 papers, 2 papers with code
Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis
This manuscript proposes a general approach for querying a causal biological knowledge graph, and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question.
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems
In contrast, structural causal models support counterfactual inference, but do not identify the mechanisms.
Crop Planning using Stochastic Visual Optimization
Given the weather and soil properties, farmers need to take critical decisions such as which seed variety to plant and in what proportion, in order to maximize productivity.
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