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A Riemannian geometry approach to reduced and discriminative covariance estimation in Brain Computer Interfaces: Github
A Riemannian geometry approach to reduced and discriminative covariance estimation in Brain Computer Interfaces: Github
The AREADNE conferences bring scientific leaders from around the world to present their recent findings on the functioning of neuronal ensembles in an informal yet spectacular setting on Santorini.
The conference series emphasizes interaction with a size and pace that encourages in-depth discussion.
Interested researchers are strongly encouraged to submit an abstract for poster presentation as attendance is strictly limited, and the conference typically sells out.
Abstract submission deadline is 24 Jan, 2020.
Send us your best work!
AREADNE 2020
Research in Encoding and Decoding of Neural Ensembles
Nomikos Conference Centre, Santorini, Greece
16-20 June 2020
http://areadne.org
info@areadne.org
Contemporary AI systems still lack high-level cognitive and learning skills. With the help of digital neuromorphic chips, scientists now aim to accurately model how humans can quickly and easily learn a cognitive task, such as a new board game.
by Tech Effects, WIRED
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