Ta-Chu Kao

11 papers A* 5Journal 6
YearRankTypeTitle / Venue / Authors
2023 A* conf
Minimum Description Length Control.
ICLR
Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matt M. Botvinick
2022 J jnl
Minimum Description Length Control.
CoRR
Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matthew M. Botvinick
2022 A* conf
iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data.
ICLR
Marine Schimel, Ta-Chu Kao, Kristopher T. Jensen, Guillaume Hennequin
2021 A* conf
Natural continual learning: success is a journey, not (just) a destination.
NeurIPS
Ta-Chu Kao, Kristopher T. Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin
2021 J jnl
Natural continual learning: success is a journey, not (just) a destination.
CoRR
Ta-Chu Kao, Kristopher T. Jensen, Alberto Bernacchia, Guillaume Hennequin
2021 A* conf
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models.
NeurIPS
Kristopher T. Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin
2020 J jnl
Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations.
CoRR
Ta-Chu Kao, Guillaume Hennequin
2020 A* conf
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data.
NeurIPS
Kristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin
2020 J jnl
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data.
CoRR
Kristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin
2019 J jnl
OwlDE: making ODEs first-class Owl citizens.
J. Open Source Softw.
Marcello Seri, Ta-Chu Kao
2017 J jnl
Layer Communities in Multiplex Networks.
CoRR
Ta-Chu Kao, Mason A. Porter