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Deka, B., Ha Nguyen, L., Amiri, S., & Goulet, J. (2022). The Gaussian multiplicative approximation for state-space models. Structural Control and Health Monitoring, 29(3), 20 pages. Lien externe
Goulet, J., Nguyen, L. H., & Amiri, S. (2021). Tractable Approximate Gaussian Inference for Bayesian Neural Networks. Journal of Machine Learning Research, 22(251), 23 pages. Lien externe
Goulet, J., & Koo, K. (2018). Empirical validation of bayesian dynamic linear models in the context of structural health monitoring. Journal of Bridge Engineering, 23(2), 1-15. Disponible
Goulet, J. (2017). Bayesian dynamic linear models for structural health monitoring. Structural Control and Health Monitoring, 24(12), e2035. Disponible
Goulet, J., Michel, C., & Kiureghian, A. D. (2015). Data-driven post-earthquake rapid structural safety assessment. Earthquake Engineering & Structural Dynamics, 44(4), 549-562. Disponible
Goulet, J., Kiureghian, A. D., & Li, B. (2015). Pre-posterior optimization of sequence of measurement and intervention actions under structural reliability constraint. Structural Safety, 52, 1-9. Disponible
Goulet, J., Texier, M., Michel, C., Smith, I. F. C., & Chouinard, L. (2014). Quantifying the effects of modeling simplifications for structural identification of bridges. Journal of Bridge Engineering, 19(1), 59-71. Disponible
Goulet, J., & Smith, I. F.C. (2013). Structural identification with systematic errors and unknown uncertainty dependencies. Computers & Structures, 128, 251-258. Disponible
Goulet, J., & Smith, I. F. C. (2013). Predicting the usefulness of monitoring for identifying the behavior of structures. Journal of Structural Engineering, 139(10), 1716-1727. Disponible
Goulet, J., & Smith, I. F. C. (2013). Performance-driven measurement system design for structural identification. Journal of Computing in Civil Engineering, 27(4), 427-436. Disponible
Goulet, J., Michel, C., & Smith, I. F.C. (2013). Hybrid probabilities and error-domain structural identification using ambient vibration monitoring. Mechanical Systems and Signal Processing, 37(1-2), 199-212. Disponible
Goulet, J., Coutu, S., & Smith, I. F.C. (2013). Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks. Advanced Engineering Informatics, 27(2), 261-269. Disponible
Goulet, J., & Smith, I. F. C. (2013). Case studies of the structural identification of bridges. Langesand Bridge. Dans Çatbaş, F. N., Kijewski-Correa, T., & Aktan, A. E. (édit.), Structural identification of constructed systems: Approaches, methods, and technologies for effective practice of St-Id (205-208). Lien externe
Goulet, J., & Smith, I. F. C. (juin 2013). Probabilistic model falsification for structural identification [Communication écrite]. 11th International Conference on Structural Safety & Reliability (ICOSSAR 2013), New York, NY. Lien externe
Goulet, J., Smith, I. F. C., Texier, M., & Chouinard, L. (mars 2012). The effects of simplifications on model predictions and consequences for model-based data interpretation [Communication écrite]. 20th Analysis and Computation Specialty Conference, Structures Congress 2012, Chicago, Illinois. Lien externe
Goulet, J. (2012). Probabilistic model falsification for infrastructure diagnosis [Thèse de doctorat, École Polytechnique Fédérale de Lausanne]. Lien externe
Goulet, J., & Smith, I. F. C. (avril 2011). Extended uniform distribution accounting for uncertainty of uncertainty [Communication écrite]. International Conference on Vulnerability and Risk Analysis and Management/Fifth International Symposium on Uncertainty Modeling and Analysis (ICVRAM-ISUMA 2011), Hyattsville, Maryland. Lien externe
Goulet, J., & Smith, I. F. C. (avril 2011). Overcoming the limitations of traditional model-updating approaches [Communication écrite]. International Conference on Vulnerability and Risk Analysis and Management/Fifth International Symposium on Uncertainty Modeling and Analysis (ICVRAM-ISUMA 2011), Hyattsville, Maryland. Lien externe
Goulet, J., & Smith, I. (décembre 2011). Prevention of over-instrumentation during the design of a monitoring system for static load tests [Communication écrite]. 5th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-5), Cancun, Mexico. Lien externe
Goulet, J., & Smith, I. F. C. (août 2011). Uncertainty corrrelation in structural performance assessment [Communication écrite]. 11th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP 2011), Zurich, Switzerland. Lien externe
Goulet, J., Kripakaran, P., & Smith, I. F. C. (2010). Multimodel structural performance monitoring. Journal of Structural Engineering, 136(10), 1309-1318. Disponible
Goulet, J., & Smith, I. F. C. (septembre 2010). CMS4SI structural identification approach for interpreting measurements [Communication écrite]. 34th IABSE Symposium, Venise, Italie. Lien externe
Goulet, J., & Smith, I. F. C. (juin 2010). Predicting usefulness of measuring structures during load tests [Communication écrite]. 13th International Conference on Structural Faults & Repair, Edinburgh, Scotland. Lien externe
Goulet, J., Kripakaran, P., & Smith, I. F. C. (juin 2009). Considering sensor characteristics during measurement-system design for structural system identification [Communication écrite]. ASCE International Workshop on Computing in Civil Engineering, Austin, Texas. Lien externe
Goulet, J., Kripakaran, P., & Smith, I. F. C. (juillet 2009). Estimation of modelling errors in structural system identification [Communication écrite]. 4th International Conference on Structural Health Monitoring on Intelligent Infrastructure (SHMII-4), Zurich, Switzerland. Lien externe
Goulet, J., Kripakaran, P., & Smith, I. F. C. (septembre 2009). Structural identification to improve bridge management [Communication écrite]. 33rd IABSE Symposium on Sustainable Infrastructure, Bangkok, Thaïlande. Lien externe
Hamida, Z., Laurent, B., & Goulet, J. (2022). OpenIPDM: A probabilistic framework for estimating the deterioration and effect of interventions on bridges. SoftwareX, 18, 101077 (6 pages). Lien externe
Hamida, Z., & Goulet, J. (2022). Quantifying the effects of interventions based on visual inspections from a network of bridges. Structure and Infrastructure Engineering, 18(8), 1222-1233. Lien externe
Hamida, Z., & Goulet, J. (2022). A stochastic model for estimating the network-scale deterioration and effect of interventions on bridges. Structural Control and Health Monitoring, 29(4), 25 pages. Lien externe
Hamida, Z., & Goulet, J. (2021). Network-scale deterioration modelling of bridges based on visual inspections and structural attributes. Structural Safety, 88, 102024 (12 pages). Lien externe
Hamida, Z., & Goulet, J. (2020). Modeling infrastructure degradation from visual inspections using network-scale state-space models. Structural Control and Health Monitoring, 27(9), 18 pages. Lien externe
Khazaeli, S., Nguyen, L. H., & Goulet, J. (2021). Anomaly detection using state-space models and reinforcement learning. Structural Control and Health Monitoring, 28(6), 23 pages. Lien externe
Luo, X., O'Brien, W. J., Leite, F., & Goulet, J. (2014). Exploring approaches to improve the performance of autonomous monitoring with imperfect data in location-aware wireless sensor networks. Advanced Engineering Informatics, 28(4), 287-296. Lien externe
Nguyen, L. H., & Goulet, J. (2022). Analytically Tractable Hidden-States Inference in Bayesian Neural Networks. Journal of Machine Learning Research, 23, 33 pages. Lien externe
Nguyen, L. H., Gaudot, I., Khazaeli, S., & Goulet, J. (2019). A Kernel-based method for modeling non-harmonic periodic phenomena in Bayesian Dynamic Linar Models. Frontiers in Built Environment, 5. Lien externe
Nguyen, L. H., & Goulet, J. (2019). Real-time anomaly detection with Bayesian dynamic linear models. Structural Control and Health Monitoring, 26(9), 17 pages. Lien externe
Nguyen, L. H., Gaudot, I., & Goulet, J. (2019). Uncertainty quantification for model parameters and hidden state variables in Bayesian dynamic linear models. Structural Control & Health Monitoring, 26(3), e2309 (20 pages). Lien externe
Nguyen, L. H., & Goulet, J. (2018). Structural health monitoring with dependence on non-harmonic periodic hidden covariates. Engineering Structures, 166, 187-194. Disponible
Nguyen, L. H., & Goulet, J. (2018). Anomaly detection with the Switching Kalman Filter for structural health monitoring. Structural Control and Health Monitoring, 25(4), 1-18. Disponible
Pasquier, R., Goulet, J., & Smith, I. F.C. (2017). Measurement system design for civil infrastructure using expected utility. Advanced Engineering Informatics, 32, 40-51. Disponible
Pasquier, R., D’Angelo, L., Goulet, J., Acevedo, C., Nussbaumer, A., & Smith, I. F. C. (2016). Measurement, data interpretation, and uncertainty propagation for fatigue assessments of structures. Journal of Bridge Engineering, 21(5), 04015087-1. Disponible
Pasquier, R., Goulet, J., Acevedo, C., & Smith, I. F. C. (2014). Improving fatigue evaluations of structures using in-service behavior measurement data. Journal of Bridge Engineering, 19(11), 1-10. Disponible
Pasquier, R., Goulet, J., & Smith, I. F. C. (juin 2013). Model-based data interpretation and diagnosis robustness [Communication écrite]. 11th International Conference on Structural Safety & Reliability (ICOSSAR 2011), New York, NY. Lien externe
Pasquier, R., Goulet, J., & Smith, I. (juillet 2012). Reducing uncertainties regarding remaining lives of structures using computer-aided data interpretation [Communication écrite]. 19th Workshop on Intelligent Computing in Engineering (EG-ICE 2012), Munich, Germany. Non disponible
Quach, A. N.-O., Tabor, L., Dumont, D., Courcelles, B., & Goulet, J. (2017). A machine learning approach for characterizing soil contamination in the presence of physical site discontinuities and aggregated samples. Advanced Engineering Informatics, 33, 60-67. Disponible
Smith, I. F. C., Goulet, J., & Laory, I. (mai 2013). Structural identification methods for full-scale bridges [Communication écrite]. Structures Congress 2013: Bridging Your Passion with Your Profession, Pittsburgh, Pennsylvania. Lien externe
Tabor, L., Goulet, J., Charron, J.-, & Desmettre, C. (2018). Probabilistic modeling of heteroscedastic laboratory experiments using Gaussian process regression. Journal of Engineering Mechanics, 144(6), 1-10. Disponible
