Ta-Chu Kao

Publications

2021.11.05

Published

iLQR-VAE: control-based learning of input-driven dynamics with applications to neural data
Marine Schimel, Ta-Chu Kao, Kristopher T. Jensen, Guillaume Hennequin
ICLR, 2022 [link]


Natural Continual Learning: success is a journey, not (just) a destination
Ta-Chu Kao, Kristopher T. Jensen, Gido M. van de Ven, Alberto Bernacchia and Guillaume Hennequin.
NeurIPs, 2021 [link | code]


Scalable Bayesian GPFA with automatic relevance determination and discrete noise models
Kristopher T. Jensen, Ta-Chu Kao, Jasmine T. Stone, and Guillaume Hennequin.
NeurIPs, 2021 [link]


Optimal anticipatory control as a theory of motor preparation: a thalamo-cortical model
Ta-Chu Kao, Mahdieh S. Sadabadi and Guillaume Hennequin.
Neuron, 2020 [link | code]


Manifold GPLVMs for discoverying non-Euclidean latent structure in neural data
Kristopher T. Jensen, Ta-Chu Kao, and Guillaume Hennequin.
NeurIPs, 2020 [link]


Neuroscience out of control: control-theoretic perspectives on neural circuit dynamics
Ta-Chu Kao and Guillaume Hennequin
Current Opinion in Neurobiology, 2019 [notebook | pdf]


OwlDE: making ODEs first-class Owl citizens
Marcello Seri and Ta-Chu Kao
Journal of Open Source Software, 2019 [link]


Null ain’t dull: new perspectives on the motor cortex
Ta-Chu Kao and Guillaume Hennequin
Trends in Cognitive Sciences, 2018 [link]


Layer Communities in Multiplex Networks
Ta-Chu Kao and Mason A. Porter
Journal of Statistical Physics, 2017 [link]

Preprints

Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations
Ta-Chu Kao and Guillaume Hennequin
arXiv link