What Did Your Adversary Believe? Optimal Filtering and Smoothing in Counter-Adversarial Autonomous Systems. - Robert Mattila; Inês Lourenço; Vikram Krishnamurthy; Cristian R. Rojas; Bo Wahlberg (CoRR, 2019)

Teaching robots to perceive time - A reinforcement learning approach (Extended version). - Inês Lourenço; Bo Wahlberg; Rodrigo Ventura 001 (CoRR, 2019)

Estimating Private Beliefs of Bayesian Agents Based on Observed Decisions. - Robert Mattila; Inês Lourenço; Cristian R. Rojas; Vikram Krishnamurthy; Bo Wahlberg (IEEE Control. Syst. Lett., 2019)

How to Protect Your Privacy? A Framework for Counter-Adversarial Decision Making. - Inês Lourenço; Robert Mattila; Cristian R. Rojas; Bo Wahlberg (CDC, 2020)

What did your adversary believeƒ Optimal Filtering and Smoothing in Counter-Adversarial Autonomous Systems. - Robert Mattila; Inês Lourenço; Vikram Krishnamurthy; Cristian R. Rojas; Bo Wahlberg (ICASSP, 2020)

Teaching Robots to Perceive Time: A Twofold Learning Approach. - Inês Lourenço; Rodrigo M. M. Ventura; Bo Wahlberg (ICDL-EPIROB, 2020)

Cooperative System Identification via Correctional Learning. - Inês Lourenço; Robert Mattila; Cristian R. Rojas; Bo Wahlberg (CoRR, 2020)

A teacher-student framework for online correctional learning. - Inês Lourenço; Rebecka Winqvist; Cristian R. Rojas; Bo Wahlberg (CoRR, 2021)

Hidden Markov Models: Inverse Filtering, Belief Estimation and Privacy Protection. - Inês Lourenço; Robert Mattila; Cristian R. Rojas; Xiaoming Hu 001; Bo Wahlberg (J. Syst. Sci. Complex., 2021)

A Teacher-Student Markov Decision Process-based Framework for Online Correctional Learning*. - Inês Lourenço; Rebecka Winqvist; Cristian R. Rojas; Bo Wahlberg (CDC, 2022)

A Biologically Inspired Computational Model of Time Perception. - Inês Lourenço; Robert Mattila; Rodrigo M. M. Ventura; Bo Wahlberg (IEEE Trans. Cogn. Dev. Syst., 2022)

Diagnosing and Repairing Feature Representations Under Distribution Shifts. - Inês Lourenço; Andreea Bobu; Cristian R. Rojas; Bo Wahlberg (CDC, 2023)

Optimal Transport for Correctional Learning. - Rebecka Winqvist; Inês Lourenço; Francesco Quinzan; Cristian R. Rojas; Bo Wahlberg (CDC, 2023)

Diagnosing and Augmenting Feature Representations in Correctional Inverse Reinforcement Learning. - Inês Lourenço; Andreea Bobu; Cristian R. Rojas; Bo Wahlberg (CoRR, 2023)