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Journal Articles
- 2019
[j1]Marcello Seri
, Ta-Chu Kao:
OwlDE: making ODEs first-class Owl citizens. J. Open Source Softw. 4(44): 1812 (2019)
Conference and Workshop Papers
- 2023
- [c5]Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matt M. Botvinick:
Minimum Description Length Control. ICLR 2023 - 2022
- [c4]Marine Schimel, Ta-Chu Kao, Kristopher T. Jensen, Guillaume Hennequin:
iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data. ICLR 2022 - 2021
- [c3]Kristopher T. Jensen, Ta-Chu Kao, Jasmine Stone, Guillaume Hennequin:
Scalable Bayesian GPFA with automatic relevance determination and discrete noise models. NeurIPS 2021: 10613-10626 - [c2]Ta-Chu Kao, Kristopher T. Jensen, Gido van de Ven, Alberto Bernacchia, Guillaume Hennequin:
Natural continual learning: success is a journey, not (just) a destination. NeurIPS 2021: 28067-28079 - 2020
- [c1]Kristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin:
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data. NeurIPS 2020
Informal and Other Publications
- 2022
- [i5]Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matthew M. Botvinick:
Minimum Description Length Control. CoRR abs/2207.08258 (2022) - 2021
- [i4]Ta-Chu Kao, Kristopher T. Jensen, Alberto Bernacchia, Guillaume Hennequin:
Natural continual learning: success is a journey, not (just) a destination. CoRR abs/2106.08085 (2021) - 2020
- [i3]Kristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin:
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data. CoRR abs/2006.07429 (2020) - [i2]Ta-Chu Kao, Guillaume Hennequin:
Automatic differentiation of Sylvester, Lyapunov, and algebraic Riccati equations. CoRR abs/2011.11430 (2020) - 2017
- [i1]Ta-Chu Kao, Mason A. Porter:
Layer Communities in Multiplex Networks. CoRR abs/1706.04147 (2017)
Coauthor Index
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