90 citations · 313 across the 14 of their papers we have counts for
15 papers
Compiling molecular ultrastructure into neural dynamics
Konrad P. Kording, Anton Arkhipov, Davy Deng +22
High-resolution brain imaging can now capture not just synapse locations but their molecular composition, with the cost of such mapping falling exponentially. Yet such ultrastructu…
Applied Astrobiology: An Integrated Approach to the Future of Life in Space
Robin Wordsworth, Collin Cherubim, Shannon Nangle +13
Searching for extraterrestrial life and supporting human life in space are traditionally regarded as separate challenges. However, there are significant benefits to an approach tha…
NeuroAI for AI Safety
Patrick Mineault, Niccolò Zanichelli, Joanne Zichen Peng +12
As AI systems become increasingly powerful, the need for safe AI has become more pressing. Humans are an attractive model for AI safety: as the only known agents capable of general…
The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions
Gal Haspel, Ben Baker, Isabel Beets +34
Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand…
Gaussian Gated Linear Networks
David Budden, Adam Marblestone, Eren Sezener +3
We propose the Gaussian Gated Linear Network (G-GLN), an extension to the recently proposed GLN family of deep neural networks. Instead of using backpropagation to learn features,…
Product Kanerva Machines: Factorized Bayesian Memory
Adam Marblestone, Yan Wu, Greg Wayne
An ideal cognitively-inspired memory system would compress and organize incoming items. The Kanerva Machine (Wu et al, 2018) is a Bayesian model that naturally implements online me…