Francesco Cadini 
- (2024): Explainability of convolutional neural networks for damage diagnosis using transmissibility functions. In: Structures, v. 69 (November 2024).
- (2024): Particle filter-based fatigue damage prognosis by fusing multiple degradation models. In: Structural Health Monitoring, v. 23, n. 5 (February 2024).
- (2024): Deep learning-based analysis to identify fluid-structure interaction effects during the response of blast-loaded plates. In: International Journal of Protective Structures, v. 15, n. 4 (February 2024).
- (2023): Enhancing Lamb wave-based damage diagnosis in composite materials using a pseudo-damage boosted convolutional neural network approach. In: Structural Health Monitoring, v. 23, n. 3 (September 2023).
- (2022): Vibration‐based structural health monitoring exploiting a combination of convolutional neural networks and autoencoders for temperature effects neutralization. In: Structural Control and Health Monitoring, v. 29, n. 11 (September 2022).
- (2022): Particle filter-based delamination shape prediction in composites subjected to fatigue loading. In: Structural Health Monitoring, v. 22, n. 3 (September 2022).
- (2022): Particle filter‐based hybrid damage prognosis considering measurement bias. In: Structural Control and Health Monitoring, v. 29, n. 4 (14 March 2022).
- (2021): On the mitigation of the RAPID algorithm uneven sensing network issue employing averaging and Gaussian blur filtering techniques. In: Composite Structures, v. 278 (December 2021).
- (2020): Fatigue damage diagnosis and prognosis of an aeronautical structure based on surrogate modelling and particle filter. In: Structural Health Monitoring, v. 20, n. 5 (December 2020).
- (2017): Advanced Monte Carlo Methods and Applications. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 3, n. 4 (December 2017).
- (2020): Global reliability sensitivity analysis by Sobol-based dynamic adaptive kriging importance sampling. In: Structural Safety, v. 87 (November 2020).
- (2019): Particle filtering‐based adaptive training of neural networks for real‐time structural damage diagnosis and prognosis. In: Structural Control and Health Monitoring, v. 26, n. 12 (12 November 2019).
- (2017): A particle filter-based model selection algorithm for fatigue damage identification on aeronautical structures. In: Structural Control and Health Monitoring, v. 24, n. 11 (November 2017).
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