Episode 41: How can deep neural networks reason

Data Science at Home - A podcast by Francesco Gadaleta

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Today’s episode  will be about deep learning and reasoning. There has been a lot of discussion about the effectiveness of deep learning models and their capability to generalize, not only across domains but also on data that such models have never seen. But there is a research group from the Department of Computer Science, Duke University that seems to be on something with deep learning and interpretability in computer vision.   References Prediction Analysis Lab Duke University https://users.cs.duke.edu/~cynthia/lab.html This looks like that: deep learning for interpretable image recognition https://arxiv.org/abs/1806.10574