Ta-Chu Kao

According to our database, Ta-Chu Kao authored at least 9 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Minimum Description Length Control.

Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matt M. Botvinick

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data.

Marine Schimel, Ta-Chu Kao, Kristopher T. Jensen, Guillaume Hennequin

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Natural continual learning: success is a journey, not (just) a destination.

Ta-Chu Kao, Kristopher T. Jensen, Alberto Bernacchia, Guillaume Hennequin

CoRR, 2021

Natural continual learning: success is a journey, not (just) a destination.

Ta-Chu Kao, Kristopher T. Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Bayesian GPFA with automatic relevance determination and discrete noise models.

Kristopher T. Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations.

Ta-Chu Kao, Guillaume Hennequin

CoRR, 2020

Manifold GPLVMs for discovering non-Euclidean latent structure in neural data.

Kristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

OwlDE: making ODEs first-class Owl citizens.

Marcello Seri, Ta-Chu Kao

J. Open Source Softw., 2019

2017

Layer Communities in Multiplex Networks.

Ta-Chu Kao, Mason A. Porter

CoRR, 2017