- Quantum-Based Combinatorial Optimization for Optimal Sensor Placement in Civil Structures. In: Structural Control and Health Monitoring, v. 2024 (January 2024). (2024):
- Characterization of the modal response using Deep recurrent neural networks. In: Engineering Structures, v. 256 (April 2022). (2022):
- A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties. In: Structural Control and Health Monitoring, v. 28, n. 10 (June 2021). (2021):
- Deep variational auto-encoders: A promising tool for dimensionality reduction and ball bearing elements fault diagnosis. In: Structural Health Monitoring, v. 18, n. 4 (April 2018). (2018):
- Deep semi-supervised generative adversarial fault diagnostics of rolling element bearings. In: Structural Health Monitoring, v. 19, n. 2 (September 2018). (2018):
- Estimating damage size and remaining useful life in degraded structures using deep learning-based multi-source data fusion. In: Structural Health Monitoring, v. 19, n. 5 (October 2019). (2019):
- Impact identification using nonlinear dimensionality reduction and supervised learning. In: Smart Materials and Structures, v. 28, n. 11 (3 October 2019). (2019):
- Convolutional neural networks for automated damage recognition and damage type identification. In: Structural Control and Health Monitoring, v. 25, n. 10 (October 2018). (2018):