Timothy J. Rogers

Orcid: 0000-0002-3433-3247

Affiliations:
  • University of Sheffield, UK


According to our database1, Timothy J. Rogers authored at least 23 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
Calibrating the Discrete Boundary Conditions of a Dynamic Simulation: A Combinatorial Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) Approach.
Sensors, August, 2024

On Gait Consistency Quantification Through ARX Residual Modeling and Kernel Two-Sample Testing.
IEEE Trans. Biomed. Eng., March, 2024

Cost-informed dimensionality reduction for structural digital twin technologies.
CoRR, 2024

Active learning for regression in engineering populations: A risk-informed approach.
CoRR, 2024

A new perspective on Bayesian Operational Modal Analysis.
CoRR, 2024

BINDy - Bayesian identification of nonlinear dynamics with reversible-jump Markov-chain Monte-Carlo.
CoRR, 2024

Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: A new full-scale dataset for structural health monitoring.
CoRR, 2024

Baseline Results for Selected Nonlinear System Identification Benchmarks.
CoRR, 2024

Probabilistic Numeric SMC Sampling for Bayesian Nonlinear System Identification in Continuous Time.
CoRR, 2024

2023
A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves.
Sensors, 2023

Sharing Information Between Machine Tools to Improve Surface Finish Forecasting.
CoRR, 2023

Full-scale modal testing of a Hawk T1A aircraft for benchmarking vibration-based methods.
CoRR, 2023

A spectrum of physics-informed Gaussian processes for regression in engineering.
CoRR, 2023

A Robust Probabilistic Approach to Stochastic Subspace Identification.
CoRR, 2023

PAO: A general particle swarm algorithm with exact dynamics and closed-form transition densities.
CoRR, 2023

2022
Physically Meaningful Uncertainty Quantification in Probabilistic Wind Turbine Power Curve Models as a Damage Sensitive Feature.
CoRR, 2022

Physics-informed machine learning for Structural Health Monitoring.
CoRR, 2022

Constraining Gaussian processes for physics-informed acoustic emission mapping.
CoRR, 2022

2021
Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm.
CoRR, 2021

Grey-box models for wave loading prediction.
CoRR, 2021

Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data.
CoRR, 2021

Structured Machine Learning Tools for Modelling Characteristics of Guided Waves.
CoRR, 2021

2020
A Bayesian methodology for localising acoustic emission sources in complex structures.
CoRR, 2020


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