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James Alexandre GouletDepartment of Civil, Geological and Mining Engineering
Profile in the Directory of Experts of Polytechnique Montréal
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Amiri, S., Goulet, J. A., Trépanier, M., Morency, C., & Saunier, N. (2023, July). Modeling transportation time series using bayesian dynamic linear models [Paper]. World Conference on Transport Research (WCTR 2023), Montréal, Québec. Published in Transportation Research Procedia, 82. Available
Deka, B., Nguyen, L. H., & Goulet, J. A. (2023). Analytically tractable heteroscedastic uncertainty quantification in Bayesian neural networks for regression tasks. Neurocomputing, 127183 (20 pages). External link
Deka, B., & Goulet, J. A. (2023). Approximate Gaussian variance inference for state-space models. International Journal of Adaptive Control and Signal Processing, 29 pages. Available
Deka, B., & Goulet, J. A. Online aleatory uncertainty quantification for probabilistic time series models [Paper]. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland (8 pages). External link
Deka, B., Ha Nguyen, L., Amiri, S., & Goulet, J. A. (2022). The Gaussian multiplicative approximation for state-space models. Structural Control and Health Monitoring, 29(3), 20 pages. External link
Deka, B., & Goulet, J. A. (2022, August). State-based Regression for Modeling the Non-linear Dependency between Time Series [Paper]. 11th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 2022), Montreal, QC, Canada. Unavailable
Fakhri, S. A. K., Hamida, Z., & Goulet, J. A. (2024). Scalable probabilistic deterioration model based on visual inspections and structural attributes from large networks of bridges. Advanced Engineering Informatics, 64, 103035 (10 pages). External link
Fakhri, S. A. K., Hamida, Z., & Goulet, J. A. (2023, July). Bayesian neural networks for large-scale infrastructure deterioration models [Paper]. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland (8 pages). Available
Goulet, J. A., & Nguyen, L. H. (2023, July). Bayesian neural networks for probabilistic surrogate models - uncertainty quantification, propagation and sensitivity analysis [Paper]. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland (8 pages). External link
Goulet, J. A., Nguyen, L. H., & Amiri, S. (2021). Tractable Approximate Gaussian Inference for Bayesian Neural Networks. Journal of Machine Learning Research, 22(251), 23 pages. External link
Goulet, J. A., & 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. Available
Goulet, J. A. (2017). Bayesian dynamic linear models for structural health monitoring. Structural Control and Health Monitoring, 24(12), e2035. Available
Goulet, J. A., Michel, C., & Kiureghian, A. D. (2015). Data-driven post-earthquake rapid structural safety assessment. Earthquake Engineering & Structural Dynamics, 44(4), 549-562. Available
Goulet, J. A., 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. Available
Goulet, J. A., 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. Available
Goulet, J. A., & Smith, I. F. C. (2013). Structural identification with systematic errors and unknown uncertainty dependencies. Computers & Structures, 128, 251-258. Available
Goulet, J. A., & Smith, I. F. C. (2013). Predicting the usefulness of monitoring for identifying the behavior of structures. Journal of Structural Engineering, 139(10), 1716-1727. Available
Goulet, J. A., & Smith, I. F. C. (2013). Performance-driven measurement system design for structural identification. Journal of Computing in Civil Engineering, 27(4), 427-436. Available
Goulet, J. A., 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. Available
Goulet, J. A., 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. Available
Goulet, J. A., & Smith, I. F. C. (2013). Case studies of the structural identification of bridges. Langesand Bridge. In Çatbaş, F. N., Kijewski-Correa, T., & Aktan, A. E. (eds.), Structural identification of constructed systems: Approaches, methods, and technologies for effective practice of St-Id (pp. 205-208). External link
Goulet, J. A., & Smith, I. F. C. (2013, June). Probabilistic model falsification for structural identification [Paper]. 11th International Conference on Structural Safety & Reliability (ICOSSAR 2013), New York, NY. External link
Goulet, J. A., Smith, I. F. C., Texier, M., & Chouinard, L. (2012, March). The effects of simplifications on model predictions and consequences for model-based data interpretation [Paper]. 20th Analysis and Computation Specialty Conference, Structures Congress 2012, Chicago, Illinois. External link
Goulet, J. A. (2012). Probabilistic model falsification for infrastructure diagnosis [Ph.D. Thesis, École Polytechnique Fédérale de Lausanne]. External link
Goulet, J. A., & Smith, I. F. C. (2011, April). Extended uniform distribution accounting for uncertainty of uncertainty [Paper]. International Conference on Vulnerability and Risk Analysis and Management/Fifth International Symposium on Uncertainty Modeling and Analysis (ICVRAM-ISUMA 2011), Hyattsville, Maryland. External link
Goulet, J. A., & Smith, I. F. C. (2011, April). Overcoming the limitations of traditional model-updating approaches [Paper]. International Conference on Vulnerability and Risk Analysis and Management/Fifth International Symposium on Uncertainty Modeling and Analysis (ICVRAM-ISUMA 2011), Hyattsville, Maryland. External link
Goulet, J. A., & Smith, I. (2011, December). Prevention of over-instrumentation during the design of a monitoring system for static load tests [Paper]. 5th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-5), Cancun, Mexico. External link
Goulet, J. A., & Smith, I. F. C. (2011, August). Uncertainty correlation in structural performance assessment [Paper]. 11th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP 2011), Zurich, Switzerland. External link
Goulet, J. A., Kripakaran, P., & Smith, I. F. C. (2010). Multimodel structural performance monitoring. Journal of Structural Engineering, 136(10), 1309-1318. Available
Goulet, J. A., & Smith, I. F. C. (2010, September). CMS4SI structural identification approach for interpreting measurements [Paper]. 34th IABSE Symposium, Venise, Italie. External link
Goulet, J. A., & Smith, I. F. C. (2010, June). Predicting usefulness of measuring structures during load tests [Paper]. 13th International Conference on Structural Faults & Repair, Edinburgh, Scotland. External link
Goulet, J. A., Kripakaran, P., & Smith, I. F. C. (2009, June). Considering sensor characteristics during measurement-system design for structural system identification [Paper]. ASCE International Workshop on Computing in Civil Engineering, Austin, Texas. External link
Goulet, J. A., Kripakaran, P., & Smith, I. F. C. (2009, July). Estimation of modelling errors in structural system identification [Paper]. 4th International Conference on Structural Health Monitoring on Intelligent Infrastructure (SHMII-4), Zurich, Switzerland. External link
Goulet, J. A., Kripakaran, P., & Smith, I. F. C. (2009, September). Structural identification to improve bridge management [Paper]. 33rd IABSE Symposium on Sustainable Infrastructure, Bangkok, Thaïlande. External link
Hamida, Z., & Goulet, J. A. (2024). Quantifying the Relative Change in Maintenance Costs due to Delayed Maintenance Actions in Transportation Infrastructure. Journal of Performance of Constructed Facilities, 38(5), 04024035 (12 pages). External link
Hamida, Z., & Goulet, J. A. (2023). Hierarchical reinforcement learning for transportation infrastructure maintenance planning. Reliability Engineering & System Safety, 235, 109214 (12 pages). External link
Hamida, Z., & Goulet, J. A. (2023, July). Maintenance planning for bridges using hierarchical reinforcement learning [Paper]. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), Dublin, Ireland (8 pages). Available
Hamida, Z., & Goulet, J. A. (2022, August). Modelling the Deterioration of Infrastructure Using Network-Scale Visual Inspections [Paper]. 11th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 2022), Montreal, QC, Canada. Unavailable
Hamida, Z., Laurent, B., & Goulet, J. A. (2022). OpenIPDM: A probabilistic framework for estimating the deterioration and effect of interventions on bridges. SoftwareX, 18, 101077 (6 pages). External link
Hamida, Z., & Goulet, J. A. (2022). Quantifying the effects of interventions based on visual inspections from a network of bridges. Structure and Infrastructure Engineering, 18(8), 1222-1233. External link
Hamida, Z., & Goulet, J. A. (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. External link
Hamida, Z., & Goulet, J. A. (2021). Network-scale deterioration modelling of bridges based on visual inspections and structural attributes. Structural Safety, 88, 102024 (12 pages). External link
Hamida, Z., & Goulet, J. A. (2020). Modeling infrastructure degradation from visual inspections using network-scale state-space models. Structural Control and Health Monitoring, 27(9), 18 pages. External link
Khazaeli, S., & Goulet, J. A. (2024). Damage detection for structural health monitoring using reinforcement and imitation learning. Structure and Infrastructure Engineering, 18 pages. External link
Khazaeli, S., Nguyen, L. H., & Goulet, J. A. (2021). Anomaly detection using state-space models and reinforcement learning. Structural Control and Health Monitoring, 28(6), 23 pages. External link
Laurent, B., Deka, B., Hamida, Z., & Goulet, J. A. (2023). Analytical Inference for Inspectors' Uncertainty Using Network-Scale Visual Inspections. Journal of Computing in Civil Engineering, 37(5), 12 pages. External link
Laurent, B., Hamida, Z., & Goulet, J. A. (2022, August). Estimating the Bias Associated with Inspectors in the Context of Visual Inspections on Infrastructure [Paper]. 11th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 2022), Montreal, QC, Canada. Unavailable
Luo, X., O'Brien, W. J., Leite, F., & Goulet, J. A. (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. External link
Nguyen, L. H., & Goulet, J. A. (2022). Analytically Tractable Hidden-States Inference in Bayesian Neural Networks. Journal of Machine Learning Research, 23(50), 33 pages. Available
Nguyen, L. H., Gaudot, I., Khazaeli, S., & Goulet, J. A. (2019). A kernel-based method for modeling non-harmonic periodic phenomena in bayesian dynamic linear models. Frontiers in Built Environment, 5, 8. Available
Nguyen, L. H., & Goulet, J. A. (2019). Real-time anomaly detection with Bayesian dynamic linear models. Structural Control and Health Monitoring, 26(9), 17 pages. External link
Nguyen, L. H., Gaudot, I., & Goulet, J. A. (2019). Uncertainty quantification for model parameters and hidden state variables in Bayesian dynamic linear models. Structural Control & Health Monitoring, 26(3), e2309 (20 pages). External link
Nguyen, L. H., & Goulet, J. A. (2018). Structural health monitoring with dependence on non-harmonic periodic hidden covariates. Engineering Structures, 166, 187-194. Available
Nguyen, L. H., & Goulet, J. A. (2018). Anomaly detection with the Switching Kalman Filter for structural health monitoring. Structural Control and Health Monitoring, 25(4), 1-18. Available
Pasquier, R., Goulet, J. A., & Smith, I. F. C. (2017). Measurement system design for civil infrastructure using expected utility. Advanced Engineering Informatics, 32, 40-51. Available
Pasquier, R., D’Angelo, L., Goulet, J. A., 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. Available
Pasquier, R., Goulet, J. A., 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. Available
Pasquier, R., Goulet, J. A., & Smith, I. F. C. (2013, June). Model-based data interpretation and diagnosis robustness [Paper]. 11th International Conference on Structural Safety & Reliability (ICOSSAR 2011), New York, NY. External link
Pasquier, R., Goulet, J. A., & Smith, I. (2012, July). Reducing uncertainties regarding remaining lives of structures using computer-aided data interpretation [Paper]. 19th Workshop on Intelligent Computing in Engineering (EG-ICE 2012), Munich, Germany. Unavailable
Quach, A. N.-O., Tabor, L., Dumont, D., Courcelles, B., & Goulet, J. A. (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. Available
Smith, I. F. C., Goulet, J. A., & Laory, I. (2013, May). Structural identification methods for full-scale bridges [Paper]. Structures Congress 2013: Bridging Your Passion with Your Profession, Pittsburgh, Pennsylvania. External link
Tabor, L., Goulet, J. A., Charron, J.-P., & Desmettre, C. (2018). Probabilistic modeling of heteroscedastic laboratory experiments using Gaussian process regression. Journal of Engineering Mechanics, 144(6), 1-10. Available
Vuong, V.-D., Nguyen, L. H., & Goulet, J. A. (2024). Coupling LSTM neural networks and state-space models through analytically tractable inference. International Journal of Forecasting, 13 pages. External link
Vuong, V.-D., & Goulet, J. A. (2022, August). Bayesian Long-Short Term Memory Neural Network for Dam Behavior Prediction [Paper]. 11th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII 2022), Montreal, QC, Canada. Unavailable
Xin, Z., & Goulet, J. A. (2024, June). Anomaly detection with switching Kalman filter and imitation learning [Paper]. 12th International Conference on Bridge Maintenance, Safety and Management (IABMAS 2024), Copenhagen, Denmark. Available
Xin, Z., & Goulet, J. A. (2024, June). Anomaly detection with switching Kalman filter and imitation [Paper]. 12th International Conference on Bridge Maintenance, Safety and Management (IABMAS 2024), Copenhagen, Denmark. Available
Xin, Z., & Goulet, J. A. (2024). Enhancing structural anomaly detection using a bounded autoregressive component. Mechanical Systems and Signal Processing, 212, 111279# (15 pages). External link
