Publications

(See also the personal webpage of our group members)

List of Publications

2024

  1. “On the equivalence of direct and indirect data-driven predictive control approaches”.
    P. Mattsson, F. Bonassi, V. Breschi, and T. B. Schön.
    IEEE Control Systems Letters, 2024
  2. “Entropy-regularized diffusion policy with q-ensembles for offline reinforcement learning”.
    R. Zhang, Z. Luo, J. Sjölund, T. B. Schön, and P. Mattsson.
    Advances in Neural Information Processing Systems (NeurIPS), 2024
  3. “Structured state-space models are deep Wiener models”.
    F. Bonassi, C. Andersson, P. Mattsson, and T. B. Schön.
    IFAC Symposium on System Identification, 2024
  4. “Automated data transfer for digital twin applications: Two case studies”.
    H. Molin, C. Wärff, E. Lindblom, M. Arnell, B. Carlsson, P. Mattsson, J. Bäckman, and U. Jeppsson.
    Water environment research, vol. 96, no. 7, p. e11074, 2024
  5. “Soft sensor for the dry solid content in thickened primary sludge”.
    H. Molin, E. Bröndum, S. Nilsson, P. Mattsson, R. Saagi, E. Lindblom, B. Carlsson, and U. Jeppsson.
    Water Science & Technology, vol. 90, no. 7, pp. 1946–1956, 2024
  6. “A model predictive control approach to motion planning in dynamic environments”.
    B. Wullt, P. Mattsson, T. B. Schön, and M. Norrlöf.
    2024 European Control Conference (ECC), 2024, pp. 3247–3254
  7. “Safe Output Feedback Improvement with Baselines”.
    R. Zhang, P. Mattsson, and D. Zachariah.
    63rd IEEE Conference on Decision and Control (CDC), 2024
  8. “Learning state observers for recurrent neural network models”.
    F. Bonassi, C. Andersson, P. Mattsson, and T. B. Schön.
    63rd IEEE Conference on Decision and Control (CDC), 2024
  9. “Regularization properties of adversarially-trained linear regression”.
    A. Ribeiro, D. Zachariah, F. Bach, and T. Schön.
    Advances in Neural Information Processing Systems, vol. 36, 2024
  10. “Adaptive robust learning using latent Bernoulli variables”.
    A. Karakulev, D. Zachariah, and P. Singh.
    Proceedings of the 41st International Conference on Machine Learning, 2024, pp. 23105–23122
  11. “Experimental Characterization of a Robust Localization Method Based on UWB Ranging”.
    V. Brunacci, A. De Angelis, and D. Zachariah.
    2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2024, pp. 1–5
  12. “Externally Valid Policy Evaluation from Randomized Trials Using Additional Observational Data”.
    S. Ek and D. Zachariah.
    The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024

2023

  1. “Regularized Linear Regression via Covariance Fitting”.
    P. Mattsson, D. Zachariah, and P. Stoica.
    IEEE Transactions on Signal Processing, vol. 71, pp. 1175–1183, 2023
  2. “Observer-Feedback-Feedforward Controller Structures in Reinforcement Learning”.
    R. Zhang, P. Mattsson, and T. Wigren.
    IFAC-PapersOnLine, vol. 56, no. 2, pp. 6247–6252, 2023
  3. “Analysis of the Minimum-Norm Least-Squares Estimator and Its Double-Descent Behavior [Lecture Notes]”.
    P. Mattsson, D. Zachariah, and P. Stoica.
    IEEE Signal Processing Magazine, vol. 40, no. 3, pp. 39–75, 2023
  4. “Robust nonlinear set-point control with reinforcement learning”.
    R. Zhang, P. Mattsson, and T. Wigren.
    2023 American Control Conference (ACC), 2023, pp. 84–91
  5. “Aiding reinforcement learning for set point control”.
    R. Zhang, P. Mattsson, and T. Wigren.
    IFAC-PapersOnLine, vol. 56, no. 2, pp. 2437–2443, 2023
  6. “On the regularization in DeePC”.
    P. Mattsson and T. B. Schön.
    IFAC-PapersOnLine, vol. 56, no. 2, pp. 625–631, 2023
  7. “Neural motion planning in dynamic environments”.
    B. Wullt, P. Mattsson, T. B. Schön, and M. Norrlöf.
    IFAC-PapersOnLine, vol. 56, no. 2, pp. 10126–10131, 2023
  8. “Prediction of on-load tap-changer switch time from vibroacoustic measurements by machine learnings”.
    J. Schiessling, P. Mattsson, E. Victorin, C. Forssén, and N. Abeywickrama.
    23rd International Symposium onHigh Voltage Engineering (ISH), 2023
  9. “Online Learning for Prediction via Covariance Fitting: Computation, Performance and Robustness”.
    M. Osama, D. Zachariah, and P. Stoica.
    Transactions on Machine Learning Research, 2023
  10. “Diagnostic Tool for Out-of-Sample Model Evaluation”.
    L. Hult, D. Zachariah, and P. Stoica.
    Transactions on Machine Learning Research, 2023
  11. “Off-Policy Evaluation with Out-of-Sample Guarantees”.
    S. Ek, D. Zachariah, F. D. Johansson, and P. Stoica.
    Transactions on Machine Learning Research, 2023
  12. “Min-Max Probe Placement and Extended Relaxation Estimation Method for Processing Blade Tip Timing Signals”.
    Z. Wang, P. Stoica, D. Zachariah, P. Babu, and Z. Yang.
    IEEE Transactions on Instrumentation and Measurement, 2023

2022

  1. “Learning Pareto-Efficient Decisions with Confidence”.
    S. Ek, D. Zachariah, and P. Stoica.
    International Conference on Artificial Intelligence and Statistics, 2022, pp. 9969–9981

2021

  1. “Bayes control of Hammerstein systems”.
    M. Ferizbegovic, P. Mattsson, T. B. Schön, and H. Hjalmarsson.
    IFAC-PapersOnLine, vol. 54, no. 7, pp. 755–760, 2021
  2. “Willems’ fundamental lemma based on second-order moments”.
    M. Ferizbegovic, H. Hjalmarsson, P. Mattsson, and T. B. Schön.
    60th IEEE Conference on Decision and Control (CDC), 2021, pp. 396–401
  3. “Robust localization in wireless networks from corrupted signals”.
    M. Osama, D. Zachariah, S. Dwivedi, and P. Stoica.
    EURASIP Journal on Advances in Signal Processing, vol. 2021, pp. 1–18, 2021
  4. “Inference of Causal Effects when Control Variables are Unknown”.
    L. Hult and D. Zachariah.
    Uncertainty in Artificial Intelligence, 2021, 2021

2020

  1. “On stability and performance of disturbance observer-based-dynamic load torque compensator for assistive exoskeleton: A hybrid approach”.
    N. Masud, P. Mattsson, C. Smith, and M. Isaksson.
    Mechatronics, vol. 69, p. 102373, 2020
  2. “Robust prediction when features are missing”.
    X. Liu, D. Zachariah, and P. Stoica.
    IEEE Signal Processing Letters, vol. 27, pp. 720–724, 2020
  3. “Learning robust decision policies from observational data”.
    M. Osama, D. Zachariah, and P. Stoica.
    Advances in Neural Information Processing Systems, vol. 33, pp. 18205–18214, 2020
  4. “Robust risk minimization for statistical learning from corrupted data”.
    M. Osama, D. Zachariah, and P. Stoica.
    IEEE Open Journal of Signal Processing, vol. 1, pp. 287–294, 2020

2019

  1. “Development and testing of full-body exoskeleton AXO-SUIT for physical assistance of the elderly”.
    S. Bai, S. Christensen, M. Islam, S. Rafique, N. Masud, P. Mattsson, L. O’Sullivan, and V. Power.
    Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics, WeRob2018, October 16-20, 2018, Pisa, Italy 3, 2019, pp. 180–184
  2. “Flexible models for smart maintenance”.
    P. Mattsson, D. Zachariah, and N. Björsell.
    IEEE International Conference on Industrial Technology (ICIT), 2019, pp. 1772–1777
  3. “Inferring heterogeneous causal effects in presence of spatial confounding”.
    M. Osama, D. Zachariah, and T. B. Schön.
    International Conference on Machine Learning, 2019, pp. 4942–4950
  4. “Learning sparse graphs for prediction of multivariate data processes”.
    A. Venkitaraman and D. Zachariah.
    IEEE Signal Processing Letters, vol. 26, no. 3, pp. 495–499, 2019
  5. “Effect inference from two-group data with sampling bias”.
    D. Zachariah and P. Stoica.
    IEEE Signal Processing Letters, vol. 26, no. 8, pp. 1103–1106, 2019
  6. “Data consistency approach to model validation”.
    A. Lindholm, D. Zachariah, P. Stoica, and T. B. Schön.
    IEEE Access, vol. 7, pp. 59788–59796, 2019
  7. “Calibration tests in multi-class classification: A unifying framework”.
    D. Widmann, F. Lindsten, and D. Zachariah.
    Advances in neural information processing systems, vol. 32, 2019
  8. “Prediction of spatial point processes: regularized method with out-of-sample guarantees”.
    M. Osama, D. Zachariah, and P. Stoica.
    Advances in Neural Information Processing Systems, vol. 32, 2019

2018

  1. “Recursive nonlinear-system identification using latent variables”.
    P. Mattsson, D. Zachariah, and P. Stoica.
    Automatica, vol. 93, pp. 343–351, 2018
  2. “Identification of cascade water tanks using a PWARX model”.
    P. Mattsson, D. Zachariah, and P. Stoica.
    Mechanical systems and signal processing, vol. 106, pp. 40–48, 2018
  3. “Nonlinear dynamics and entrainment in a continuously forced pulse-modulated model of testosterone regulation”.
    A. Medvedev, P. Mattsson, Z. T. Zhusubaliyev, and V. Avrutin.
    Nonlinear dynamics, vol. 94, pp. 1165–1181, 2018
  4. “Development and Testing of Full-Body Exoskeleton AXO-SUIT for Physical Assistance of the Elderly”.
    P. Mattsson, L. O’Sullivan, and V. Power.
    Wearable Robotics: Challenges and Trends: Proceedings of the 4th International Symposium on Wearable Robotics, WeRob2018, October 16-20, 2018, Pisa, Italy, 2018, vol. 22, p. 180
  5. “Identification of Nonlinear Feedback Mechanisms Operating in Closed Loop using Inertial Sensors”.
    F. Olsson, K. Halvorsen, D. Zachariah, and P. Mattsson.
    IFAC-PapersOnLine, vol. 51, no. 15, pp. 473–478, 2018
  6. “Regularized parametric system identification: a decision-theoretic formulation”.
    J. Wågberg, D. Zachariah, and T. B. Schön.
    2018 Annual American Control Conference (ACC), 2018, pp. 1895–1900
  7. “Learning localized spatio-temporal models from streaming data”.
    M. Osama, D. Zachariah, and T. Schön.
    International Conference on Machine Learning, 2018, pp. 3927–3935
  8. “Reliable semi-supervised learning when labels are missing at random”.
    X. Liu, D. Zachariah, J. Wågberg, and T. B. Schön.
    arXiv preprint arXiv:1811.10947, 2018

2017

  1. “Nonlinear system identification of the dissolved oxygen to effluent ammonia dynamics in an activated sludge process”.
    T. Chistiakova, P. Mattsson, B. Carlsson, and T. Wigren.
    IFAC-PapersOnLine, vol. 50, no. 1, pp. 3917–3922, 2017
  2. “Prediction performance after learning in Gaussian process regression”.
    J. Wagberg, D. Zachariah, T. Schon, and P. Stoica.
    Artificial Intelligence and Statistics, 2017, pp. 1264–1272
  3. “Scalable and passive wireless network clock synchronization in LOS environments”.
    D. Zachariah, S. Dwivedi, P. Händel, and P. Stoica.
    IEEE Transactions on Wireless Communications, vol. 16, no. 6, pp. 3536–3546, 2017
  4. “Comments on ‘enhanced PUMA for direction-of-arrival estimation and its performance analysis’”.
    D. Zachariah, P. Stoica, and M. Jansson.
    IEEE Transactions on Signal Processing, vol. 65, no. 22, pp. 6113–6114, 2017

2016

  1. “Convergence analysis for recursive Hammerstein identification”.
    P. Mattsson and T. Wigren.
    Automatica, vol. 71, pp. 179–186, 2016
  2. “Recursive identification method for piecewise ARX models: A sparse estimation approach”.
    P. Mattsson, D. Zachariah, and P. Stoica.
    IEEE Transactions on Signal Processing, vol. 64, no. 19, pp. 5082–5093, 2016
  3. “Cascaded tanks benchmark combining soft and hard nonlinearities”.
    M. Schoukens, P. Mattsson, T. Wigren, and J.-P. Noël.
    Workshop on nonlinear system identification benchmarks, 2016, pp. 20–23
  4. “Pulse-modulated model of testosterone regulation subject to exogenous signals”.
    P. Mattsson, A. Medvedev, and Z. T. Zhusubaliyev.
    2016 IEEE 55th Conference on Decision and Control (CDC), 2016, pp. 5023–5028
  5. “Online prediction of spatial fields for radio-frequency communication”.
    D. Zachariah, N. Jaldén, and P. Stoica.
    2016 24th European Signal Processing Conference (EUSIPCO), 2016, pp. 1252–1256
  6. “Pearson information-based lower bound on Fisher information”.
    D. Zachariah and P. Stoica.
    arXiv preprint arXiv:1611.07712, 2016

2015

  1. “Modeling of testosterone regulation by pulse-modulated feedback”.
    P. Mattsson and A. Medvedev.
    Signal and Image Analysis for Biomedical and Life Sciences, pp. 23–40, 2015
  2. “Joint ranging and clock parameter estimation by wireless round trip time measurements”.
    S. Dwivedi, A. De Angelis, D. Zachariah, and P. Händel.
    IEEE Journal on Selected Areas in Communications, vol. 33, no. 11, pp. 2379–2390, 2015
  3. “Cramer-Rao Bound Analog of Bayes Rule [Lecture Notes]”.
    D. Zachariah and P. Stoica.
    Signal Processing Magazine, IEEE, vol. 32, no. 2, pp. 164–168, 2015
  4. “Online hyperparameter-free sparse estimation method”.
    D. Zachariah and P. Stoica.
    IEEE Transactions on Signal Processing, vol. 63, no. 13, pp. 3348–3359, 2015

2014

  1. “Recursive identification of Hammerstein models”.
    P. Mattsson and T. Wigren.
    2014 American Control Conference, 2014, pp. 2498–2503
  2. “Discrete-time modeling of a hereditary impulsive feedback system”.
    A. Churilov, A. Medvedev, and P. Mattsson.
    53rd IEEE Conference on Decision and Control, 2014, pp. 765–770
  3. “Estimation for the Linear Model with Uncertain Covariance Matrices”.
    D. Zachariah, N. Shariati, M. Bengtsson, M. Jansson, and S. Chatterjee.
    IEEE Transactions on Signal Processing, vol. 62, no. 6, pp. 1525–1535, 2014
  4. “Schedule-based sequential localization in asynchronous wireless networks”.
    D. Zachariah, A. D. Angelis, S. Dwivedi, and P. Händel.
    EURASIP Journal on Advances in Signal Processing, vol. 2014, pp. 1–12, 2014

2013

  1. “State estimation in linear time-invariant systems with unknown impulsive inputs”.
    P. Mattsson and A. Medvedev.
    2013 European Control Conference (ECC), 2013, pp. 1675–1680
  2. “Periodical solutions in a pulse-modulated model of endocrine regulation with time-delay”.
    A. Churilov, A. Medvedev, and P. Mattsson.
    IEEE Transactions on Automatic Control, vol. 59, no. 3, pp. 728–733, 2013
  3. “Modeling of testosterone regulation by pulse-modulated feedback: an experimental data study”.
    P. Mattsson and A. Medvedev.
    AIP Conference Proceedings, 2013, vol. 1559, no. 1, pp. 333–342
  4. “Finite-dimensional reducibility of time-delay systems under pulse-modulated feedback”.
    A. Churilov, A. Medvedev, and P. Mattsson.
    52nd IEEE Conference on Decision and Control, 2013, pp. 2078–2083
  5. “Self-localization of asynchronous wireless nodes with parameter uncertainties”.
    D. Zachariah, A. De Angelis, S. Dwivedi, and P. Händel.
    IEEE Signal Processing Letters, vol. 20, no. 6, pp. 551–554, 2013
  6. “Line spectrum estimation with probabilistic priors”.
    D. Zachariah, P. Wirfält, M. Jansson, and S. Chatterjee.
    Signal Processing, vol. 93, no. 11, pp. 2969–2974, 2013
  7. “Cooperative Decentralized Localization Using Scheduled Wireless Transmissions”.
    S. Dwivedi, D. Zachariah, A. De Angelis, and P. Hendel.
    2013
  8. “Utilization of noise-only samples in array processing with prior knowledge”.
    D. Zachariah, M. Jansson, and M. Bengtsson.
    IEEE Signal Processing Letters, vol. 20, no. 9, pp. 865–868, 2013
  9. “Enhanced Capon beamformer using regularized covariance matching”.
    D. Zachariah, M. Jansson, and S. Chatterjee.
    2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013, pp. 97–100

2012

  1. “Estimation of input impulses by means of continuous finite memory observers”.
    P. Mattsson and A. Medvedev.
    2012 American Control Conference (ACC), 2012, pp. 6769–6774
  2. “Analysis of a pulse-modulated model of endocrine regulation with time-delay”.
    A. Churilov, A. Medvedev, and P. Mattsson.
    2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012, pp. 362–367
  3. “Periodical solutions in a time-delay model of endocrine regulation by pulse-modulated feedback”.
    A. Churilov, A. Medvedev, and P. Mattsson.
    Proceedings of the 51st IEEE Conference on Decision and Control, 2012, pp. 362–367