msDyNODE captures the Lorenz attractor parameters.

msDyNODE captures the Lorenz attractor parameters.

<p>The predictions are summarized from 10 repeats of model training individually.</p>

Saved in:

Bibliographic Details
Main Author:	Yin-Jui Chang (7435466) (author)
Other Authors:	Yuan-I Chen (4578928) (author), Hannah M. Stealey (20384277) (author), Yi Zhao (14034) (author), Hung-Yun Lu (20384280) (author), Enrique Contreras-Hernandez (20384283) (author), Megan N. Baker (20384286) (author), Edward Castillo (10284715) (author), Hsin-Chih Yeh (61739) (author), Samantha R. Santacruz (20384289) (author)
Published:	2024
Subjects:	Biophysics Genetics Neuroscience Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified mechanistic multiscale studies despite recent advances derived causal interactions collective activity represented n </ u e </ u dy </ u div >< p </ u population activity brain activity work offers underlying directionality recording locations new approach neural signals neural mechanisms multimodal measurements hierarchical neuroanatomy electrophysiological experiments cale neural aligned well
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Cannot write session to /tmp/vufind_sessions/sess_t4u8gbbsntjegfpldsu1745ads