Ricardo Vinuesa
Orcid: 0000-0001-6570-5499
According to our database1,
Ricardo Vinuesa
authored at least 49 papers
between 2019 and 2024.
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Bibliography
2024
Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks.
Expert Syst. Appl., 2024
2023
Technol. Knowl. Learn., March, 2023
Higher-order dynamic mode decomposition on-the-fly: A low-order algorithm for complex fluid flows.
J. Comput. Phys., February, 2023
Frontiers Comput. Sci., 2023
Active flow control for three-dimensional cylinders through deep reinforcement learning.
CoRR, 2023
β-Variational autoencoders and transformers for reduced-order modelling of fluid flows.
CoRR, 2023
Effective control of two-dimensional Rayleigh-Bénard convection: invariant multi-agent reinforcement learning is all you need.
CoRR, 2023
Closing the gap between research and projects in climate change innovation in Europe.
CoRR, 2023
CoRR, 2023
Get Out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
2022
In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst.
J. Supercomput., 2022
Softw. Pract. Exp., 2022
Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection.
Sensors, 2022
The Role of Robotics in Achieving the United Nations Sustainable Development Goals - The Experts' Meeting at the 2021 IEEE/RSJ IROS Workshop [Industry Activities].
IEEE Robotics Autom. Mag., 2022
Nat. Comput. Sci., 2022
An uncertainty-quantification framework for assessing accuracy, sensitivity, and robustness in computational fluid dynamics.
J. Comput. Sci., 2022
Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems.
J. Comput. Phys., 2022
Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula.
J. Artif. Intell. Res., 2022
Log. J. IGPL, 2022
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows.
Expert Syst. Appl., 2022
Comput. Sci. Eng., 2022
The Sustainable Development Goals and Aerospace Engineering: A critical note through Artificial Intelligence.
CoRR, 2022
Physics-Informed Transfer Learning Strategy to Accelerate Unsteady Fluid Flow Simulations.
CoRR, 2022
CoRR, 2022
CoRR, 2022
The potential of artificial intelligence for achieving healthy and sustainable societies.
CoRR, 2022
IEEE Access, 2022
2021
Data deprivations, data gaps and digital divides: Lessons from the COVID-19 pandemic.
Big Data Soc., July, 2021
Interpretable deep-learning models to help achieve the Sustainable Development Goals.
Nat. Mach. Intell., 2021
Acquisition and User Behavior in Online Science Laboratories before and during the COVID-19 Pandemic.
Multimodal Technol. Interact., 2021
UQit: A Python package for uncertainty quantification (UQ) in computational fluid dynamics (CFD).
J. Open Source Softw., 2021
CoRR, 2021
Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression.
CoRR, 2021
Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations.
CoRR, 2021
COVID-19 Digital Contact Tracing Applications and Techniques: A Review Post Initial Deployments.
CoRR, 2021
2020
Recurrent neural networks and Koopman-based frameworks for temporal predictions in turbulence.
CoRR, 2020
CoRR, 2020
2019
CoRR, 2019
Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder.
Proceedings of the 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), 2019
Proceedings of the 9th IEEE Symposium on Large Data Analysis and Visualization, 2019