Podknife - BI 011 Grace Lindsay: Visual Attention in CNNs by Brain Inspired

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BI 011 Grace Lindsay: Visual Attention in CNNs

Podcast |: Brain Inspired
Publisher |: Paul Middlebrooks
Media Type |: audio
Podknife tags |: Artificial Intelligence,; Data Science,; Interview,; Machine Learning,; Neuroscience,; Philosophy,; Psychology,; Science & Medicine,; Technology
Categories Via RSS |: Education,; Natural Sciences,; Science,; Technology
Publication Date |: Sep 27, 2018
Episode Duration |: 00:50:30

Description
Content Encoded

Grace shares her recent work adding an attention signal to convolutional neural networks - ones that emulate the ventral visual stream in the brain - to test the "feature gain similarity" model of attention. Lots more, of course. Click the show to access the show notes.

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Mentioned in the show:

The paper we discuss: How biological attention mechanisms improve task performance in a large-scale visual system model.
Follow Grace on Twitter: @neurograce.
She co-hosts the AI/Neuroscience/Science podcast, Unsupervised Thinking.
Her excellent blog Neurdiness.
- The CNN blog post I highly recommend for a deeper dive: Deep Convolutional Neural Networks as Models of the Visual System: Q&A.
Or listen to my interview with Dan Yamins.
The podcast that inspired Grace’s Unsupervised Thinking podcast: Partially Examined Life.
The (famous) Cocktail Party Effect.
3 excellent books by Yuval Noah Harari (whose name I mar) I mention in passing:

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