Inferring Latent Dynamics Underlying Neural Population Activity Via
An important problem in systems neuroscience is to identify the latent dynamics underlying neural population activity Here we address this problem by introducing a low dimensional nonlinear
Inferring Latent Dynamics Underlying Neural Population Activity Via , This work introduces a novel approach to learning low dimensional approximations of neural dynamics by using a sequential variational autoencoder that represents the latent dynamical
Inferring Latent Dynamics Underlying Neural Population Activity Via
Here we address this prob lem by introducing a low dimensional nonlinear model for latent neural population dynamics us ing neural ordinary differential equations neural ODEs with noisy
Inferring Latent Dynamics Underlying Neural Population Activity Via , This work introduces a novel approach to learning low dimensional approximations of neural dynamics by using a sequential variational autoencoder that represents the latent dynamical
ICML 2021 Inferring Latent Dynamics Underlying Neural Population
ICML 2021 Inferring Latent Dynamics Underlying Neural Population , An important problem in systems neuroscience is to identify the latent dynamics underlying neural population activity Here we address this problem by introducing a low dimensional nonlinear
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Track Applications Bio 1 International Conference On Machine Learning
Track Applications Bio 1 International Conference On Machine Learning Jul 21 2021 nbsp 0183 32 An important problem in systems neuroscience is to identify the latent dynamics underlying neural population activity Here we address this problem by introducing a low
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Title Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations author Kim Timothy Doyeon and Luo Thomas Zhihao and Pillow Jonathan W Poisson Latent Neural Differential Equations PLNDE GitHub. Timothy D Kim Thomas Z Luo Jonathan W Pillow and Carlos Brody quot Inferring latent dynamics underlying neural population activity via neural differential equations quot Here we address this problem by introducing a low dimensional nonlinear model for latent neural population dynamics using neural ordinary differential equations neural ODEs with noisy
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