 | Monter d'un niveau |
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). Lien externe
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. Lien externe
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. Lien externe
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. Disponible
Nguyen, L. H. (2019). Real-time Anomaly Detection in the Behaviour of Structures [Thèse de doctorat, Polytechnique Montréal]. Disponible
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. Disponible
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. Lien externe
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). Lien externe
Nguyen, L. H., & Goulet, J. A. (2018). Structural health monitoring with dependence on non-harmonic periodic hidden covariates. Engineering Structures, 166, 187-194. Disponible
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. Disponible
