Inês Lourenço
Cited by
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Estimating private beliefs of Bayesian agents based on observed decisions
R Mattila, I Lourenço, CR Rojas, V Krishnamurthy, B Wahlberg
IEEE Control Systems Letters 3 (3), 523-528, 2019
How to protect your privacy? A framework for counter-adversarial decision making
I Lourenço, R Mattila, CR Rojas, B Wahlberg
2020 59th IEEE Conference on Decision and Control (CDC), 1785-1791, 2020
What did your adversary believe? Optimal filtering and smoothing in counter-adversarial autonomous systems
R Mattila, I Lourenço, V Krishnamurthy, CR Rojas, B Wahlberg
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Hidden Markov models: inverse filtering, belief estimation and privacy protection
I Lourenço, R Mattila, CR Rojas, X Hu, B Wahlberg
Journal of Systems Science and Complexity 34, 1801-1820, 2021
Cooperative system identification via correctional learning
I Lourenço, R Mattila, CR Rojas, B Wahlberg
19th IFAC Symposium on System Identification (SYSID) 54 (7), 19-24, 2021
A teacher-student Markov Decision Process-based framework for online correctional learning
I Lourenço, R Winqvist, CR Rojas, B Wahlberg
2022 IEEE 61st Conference on Decision and Control (CDC), 3456-3461, 2022
A Biologically Inspired Computational Model of Time Perception
I Lourenço, R Mattila, R Ventura, B Wahlberg
IEEE Transactions on Cognitive and Developmental Systems 14 (2), 258-268, 2021
Teaching robots to perceive time: A twofold learning approach
I Lourenço, R Ventura, B Wahlberg
2020 Joint IEEE 10th International Conference on Development and Learning …, 2020
Diagnosing and Augmenting Feature Representations in Correctional Inverse Reinforcement Learning
I Lourenço, A Bobu, CR Rojas, B Wahlberg
arXiv preprint arXiv:2304.05238, 2023
Optimal Transport for Correctional Learning
R Winqvist, I Lourenco, F Quinzan, CR Rojas, B Wahlberg
arXiv preprint arXiv:2304.01701, 2023
Forward and Inverse Decision-Making in Adversarial, Cooperative, and Biologically-Inspired Dynamical Systems
I de Miranda de Matos Lourenço
KTH Royal Institute of Technology, 2021
Teaching robots to perceive time - A reinforcement learning approach (Extended version)
I Lourenço, B Wahlberg, R Ventura
arXiv preprint arXiv:1912.10113, 2019
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