Daniel Pfrommer

Zehao Dou

Christopher Scarvelis

CoRR, December, 2025

Much Ado About Noising: Dispelling the Myths of Generative Robotic Control.

[BibT_eX]

[DOI]

CoRR, December, 2025

The Pitfalls of Imitation Learning when Actions are Continuous.

[BibT_eX]

[DOI]

CoRR, March, 2025

The title of the paper.

[BibT_eX]

[DOI]

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

A Test-Function Approach to Incremental Stability.

[BibT_eX]

[DOI]

Proceedings of the 64th IEEE Conference on Decision and Control, 2025

2024

Improved Sample Complexity of Imitation Learning for Barrier Model Predictive Control.

[BibT_eX]

[DOI]

CoRR, 2024

On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control.

[BibT_eX]

[DOI]

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

2023

Imitating Complex Trajectories: Bridging Low-Level Stability and High-Level Behavior.

[BibT_eX]

[DOI]

Adam Block

CoRR, 2023

Smooth Model Predictive Control with Applications to Statistical Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Linear Variational State Space Filtering.

[BibT_eX]

[DOI]

Nikolai Matni

CoRR, 2022

TaSIL: Taylor Series Imitation Learning.

[BibT_eX]

[DOI]