Sebastian Curi

According to our database1, Sebastian Curi authored at least 19 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Get Back Here: Robust Imitation by Return-to-Distribution Planning.
CoRR, 2023

Gradient-Based Trajectory Optimization With Learned Dynamics.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
Epistemic Uncertainty for Practical Deep Model-Based Reinforcement Learning.
PhD thesis, 2022

Constrained Policy Optimization via Bayesian World Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Safe Reinforcement Learning via Confidence-Based Filters.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Risk-Averse Offline Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Logistic Q-Learning.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory.
CoRR, 2020

Adaptive Sampling for Stochastic Risk-Averse Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Structured Variational Inference in Partially Observable UnstableGaussian Process State Space Models.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

2019
Structured Variational Inference in Unstable Gaussian Process State Space Models.
CoRR, 2019

Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Online Variance Reduction with Mixtures.
Proceedings of the 36th International Conference on Machine Learning, 2019

Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
Unsupervised Imitation Learning.
CoRR, 2018

2017
Control of low-inertia power grids: A model reduction approach.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017


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