Latest Episodes
BI 011 Grace Lindsay: Visual Attention in CNNs
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...
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BI 010 Adam Marblestone: Brain Cost Functions
Mentioned in the show Adam’s Website. Follow him on Twitter. He made Technology Review’s 35 Innovators Under 35. The paper we discuss: Toward an...
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BI 009 Blake Richards: Deep Learning in the Brain
Mentioned in the show Follow Blake on twitter: @tyrell_turing Blake’s Learning in Neural Circuits (LiNC) Laboratory. He’s a Fellow with the Learning in Machines...
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BI 008 Joshua Glaser: Supervised ML for Neuroscience
Mentioned in the show The two papers we discuss: The Roles of Supervised Machine Learning in Systems Neuroscience Machine learning for neural decoding Kording...
BI 007 Daniel Yamins: Infant AI and CNNs
Mentioned in the show: Dan’s Stanford Neuroscience and Artificial Intelligence Laboratory: The 2 papers we discuss Performance-optimized hierarchical models predict neural responses in higher...
BI 006 Ryan Poplin: Deep Solutions
[bctt tweet="Check out episode 6 of the Brain Inspired podcast: Deep learning, eyeballs, and brains" username="pgmid"] Mentioned in the show Ryan Poplin What is...