DeepAgg

An implementation of the crowdsourced aggregation network proposed in the paper

“Alex Gaunt, Diana Borsa, and Yoram Bachrach. 2016. Training deep neural nets to aggregate crowdsourced responses. In Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence (UAI’16), Alexander Ihler and Dominik Janzing (Eds.). AUAI Press, Arlington, Virginia, United States, 242-251.”

The implementation also contains an extension to the proposed model, by adding a third dimension to account for the multiple-correct answer scenario.

This was used for experimenting in the initial stages for the Fast Dawid-Skene project.

This implementation is written in Python.

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