Kristopher T. Jensen

According to our database, Kristopher T. Jensen authored at least 9 papers between 2020 and 2024.

Collaborative distances:

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

2024

A neural network model trained on free recall learns the method of loci.

Moufan Li, Kristopher T. Jensen, Marcelo G. Mattar

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

Some and Done? Temporally extended decisions with very few rollouts.

Sixing Chen, Kristopher T. Jensen, Marcelo G. Mattar

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

2023

An introduction to reinforcement learning for neuroscience.

Kristopher T. Jensen

CoRR, 2023

Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles.

Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin Adric Dunn

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

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