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2020 – today
- 2024
[j20]Aniel Jardines
, Hamidreza Eivazi, Elias Zea, Javier García-Heras, Juan Simarro, Evelyn Otero, Manuel Soler, Ricardo Vinuesa:
Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks. Expert Syst. Appl. 241: 122466 (2024)- [c7]Pratibha Raghupati Hegde, Oleksandr Kyriienko, Hermanni Heimonen, Panagiotis Tolias, Gilbert Netzer, Panagiotis Kl. Barkoutsos, Ricardo Vinuesa, Ivy Peng, Stefano Markidis:
Beyond the Buzz: Strategic Paths for Enabling Useful NISQ Applications. CF 2024 - [c6]Konstantina Koliogeorgi, George Anagnostopoulos, Gerardo Zampino, Marcial Sanchis, Ricardo Vinuesa, Sotirios Xydis:
Auto-tuning Multi-GPU High-Fidelity Numerical Simulations for Urban Air Mobility. DATE 2024: 1-6 - [c5]Jonah Ekelund, Ricardo Vinuesa, Yuri V. Khotyaintsev, Pierre Henri, Gian Luca Delzanno, Stefano Markidis:
AI in Space for Scientific Missions: Strategies for Minimizing Neural-Network Model Upload. e-Science 2024: 1-10 - [c4]Alfred Nilsson, Klas Wijk, Sai Bharath Chandra Gutha, Erik Englesson, Alexandra Hotti, Carlo Saccardi, Oskar Kviman, Jens Lagergren, Ricardo Vinuesa, Hossein Azizpour:
Indirectly Parameterized Concrete Autoencoders. ICML 2024 - [i36]Alfred Nilsson, Klas Wijk, Sai Bharath Chandra Gutha, Erik Englesson, Alexandra Hotti, Carlo Saccardi, Oskar Kviman, Jens Lagergren, Ricardo Vinuesa, Hossein Azizpour:
Indirectly Parameterized Concrete Autoencoders. CoRR abs/2403.00563 (2024) - [i35]Ricardo Vinuesa, Jean Rabault, Hossein Azizpour, Stefan Bauer, Bingni W. Brunton, Arne Elofsson, Elias Jarlebring, Hedvig Kjellström, Stefano Markidis, David Marlevi, Paola Cinnella, Steven L. Brunton:
Opportunities for machine learning in scientific discovery. CoRR abs/2405.04161 (2024) - [i34]Sunwoong Yang, Ricardo Vinuesa, Namwoo Kang:
Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction. CoRR abs/2406.03789 (2024) - [i33]Jonah Ekelund, Ricardo Vinuesa, Yuri V. Khotyaintsev, Pierre Henri, Gian Luca Delzanno, Stefano Markidis:
AI in Space for Scientific Missions: Strategies for Minimizing Neural-Network Model Upload. CoRR abs/2406.14297 (2024) - [i32]Klas Wijk, Ricardo Vinuesa, Hossein Azizpour:
Revisiting Score Function Estimators for k-Subset Sampling. CoRR abs/2407.16058 (2024) - [i31]Joogoo Jeon, Jean Rabault, Joel Vasanth, Francisco Alcántara-Ávila, Shilaj Baral, Ricardo Vinuesa:
Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality. CoRR abs/2407.17822 (2024) - [i30]Sai Bharath Chandra Gutha, Hossein Azizpour, Ricardo Vinuesa:
Inverse Problems with Diffusion Models: A MAP Estimation Perspective. CoRR abs/2407.20784 (2024) - [i29]Joel Vasanth, Jean Rabault, Francisco Alcántara-Ávila, Mikael Mortensen, Ricardo Vinuesa:
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection. CoRR abs/2407.21565 (2024) - [i28]Andres Cremades, Sergio Hoyas, Ricardo Vinuesa:
Additive-feature-attribution methods: a review on explainable artificial intelligence for fluid dynamics and heat transfer. CoRR abs/2409.11992 (2024) - 2023
- [j19]Kevin Baum, Joanna Bryson, Frank Dignum, Virginia Dignum, Marko Grobelnik, Holger H. Hoos, Morten Irgens, Paul Lukowicz, Catelijne Muller, Francesca Rossi, John Shawe-Taylor, Andreas Theodorou, Ricardo Vinuesa:
From fear to action: AI governance and opportunities for all. Frontiers Comput. Sci. 5 (2023) - [j18]Christian Amor, Philipp Schlatter, Ricardo Vinuesa, Soledad Le Clainche:
Higher-order dynamic mode decomposition on-the-fly: A low-order algorithm for complex fluid flows. J. Comput. Phys. 475: 111849 (2023) - [j17]Clarissa Hedenqvist, Mario Romero, Ricardo Vinuesa:
Improving the Learning of Mechanics Through Augmented Reality. Technol. Knowl. Learn. 28(1): 347-368 (2023) - [c3]Rana Tallal Javed, Osama Nasir, Melania Borit, Loïs Vanhée, Elias Zea, Shivam Gupta, Ricardo Vinuesa, Junaid Qadir:
Get Out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula (Extended Abstract). IJCAI 2023: 6905-6909 - [i27]Andres Cremades, Sergio Hoyas, Pedro Quintero, Martin Lellep, Moritz Linkmann, Ricardo Vinuesa:
Explaining wall-bounded turbulence through deep learning. CoRR abs/2302.01250 (2023) - [i26]Ricardo Vinuesa, Steven L. Brunton, Beverley J. McKeon:
The transformative potential of machine learning for experiments in fluid mechanics. CoRR abs/2303.15832 (2023) - [i25]Francesca Larosa, Jaroslav Mysiak, Marco Molinari, Panagiotis Varelas, Haluk Akay, Will McDowall, Catalina Spadaru, Francesco Fuso Nerini, Ricardo Vinuesa:
Closing the gap between research and projects in climate change innovation in Europe. CoRR abs/2303.17560 (2023) - [i24]Colin Vignon, Jean Rabault, Joel Vasanth, Francisco Alcántara-Ávila, Mikael Mortensen, Ricardo Vinuesa:
Effective control of two-dimensional Rayleigh-Bénard convection: invariant multi-agent reinforcement learning is all you need. CoRR abs/2304.02370 (2023) - [i23]Alberto Solera-Rico, Carlos Sanmiguel Vila, M. A. Gómez, Yuning Wang, Abdulrahman Almashjary, Scott T. M. Dawson, Ricardo Vinuesa:
β-Variational autoencoders and transformers for reduced-order modelling of fluid flows. CoRR abs/2304.03571 (2023) - [i22]Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge:
Discovering Causal Relations and Equations from Data. CoRR abs/2305.13341 (2023) - [i21]Marcial Sanchis-Agudo, Yuning Wang, Karthik Duraisamy, Ricardo Vinuesa:
Easy attention: A simple self-attention mechanism for Transformers. CoRR abs/2308.12874 (2023) - [i20]Pol Suárez, Francisco Alcántara-Ávila, Arnau Miró, Jean Rabault, Bernat Font, Oriol Lehmkuhl, Ricardo Vinuesa:
Active flow control for three-dimensional cylinders through deep reinforcement learning. CoRR abs/2309.02462 (2023) - 2022
- [j16]Raghu Raman, Prashasti Singh, Vivek Kumar Singh, Ricardo Vinuesa, Prema Nedungadi:
Understanding the Bibliometric Patterns of Publications in IEEE Access. IEEE Access 10: 35561-35577 (2022) - [j15]Ricardo Vinuesa, Steven L. Brunton:
Emerging Trends in Machine Learning for Computational Fluid Dynamics. Comput. Sci. Eng. 24(5): 33-41 (2022) - [j14]Hamidreza Eivazi, Soledad Le Clainche, Sergio Hoyas, Ricardo Vinuesa:
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows. Expert Syst. Appl. 202: 117038 (2022) - [j13]Christian Amor, José Miguel Pérez, Philipp Schlatter, Ricardo Vinuesa, Soledad Le Clainche:
Modeling the Turbulent Wake Behind a Wall-Mounted Square Cylinder. Log. J. IGPL 30(2): 263-276 (2022) - [j12]Rana Tallal Javed, Osama Nasir, Melania Borit, Loïs Vanhée, Elias Zea, Shivam Gupta, Ricardo Vinuesa, Junaid Qadir:
Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula. J. Artif. Intell. Res. 73: 933-965 (2022) - [j11]Yuki Morita, Saleh Rezaeiravesh, N. Tabatabaei, Ricardo Vinuesa, Koji Fukagata, Philipp Schlatter:
Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems. J. Comput. Phys. 449: 110788 (2022) - [j10]Saleh Rezaeiravesh, Ricardo Vinuesa, Philipp Schlatter:
An uncertainty-quantification framework for assessing accuracy, sensitivity, and robustness in computational fluid dynamics. J. Comput. Sci. 62: 101688 (2022) - [j9]Ricardo Vinuesa, Steven L. Brunton:
Enhancing computational fluid dynamics with machine learning. Nat. Comput. Sci. 2(6): 358-366 (2022) - [j8]Vincent Mai, Bram Vanderborght, Tamás Haidegger, Alaa M. Khamis, Niraj Bhargava, Dominik B. O. Boesl, Katleen Gabriels, An Jacobs, AJung Moon, Robin R. Murphy, Yasushi Nakauchi, Edson Prestes, Rao R. Bhavani, Ricardo Vinuesa, Carl-Maria Mörch:
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. 29(1): 92-107 (2022) - [j7]Dmytro Mamchur, Janis Peksa, Soledad Le Clainche, Ricardo Vinuesa:
Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection. Sensors 22(6): 2121 (2022) - [j6]Sukhpal Singh Gill, Ricardo Vinuesa, Venki Balasubramanian, Soumya K. Ghosh:
Innovative software systems for managing the impact of the COVID-19 pandemic. Softw. Pract. Exp. 52(4): 821-823 (2022) - [j5]Marco Atzori, Wiebke Köpp, Steven Wei Der Chien, Daniele Massaro, Fermín Mallor, Adam Peplinski, Mohamad Rezaei, Niclas Jansson, Stefano Markidis, Ricardo Vinuesa, Erwin Laure, Philipp Schlatter, Tino Weinkauf:
In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst. J. Supercomput. 78(3): 3605-3620 (2022) - [i19]Beril Sirmaçek, S. Gupta, Fermín Mallor, Hossein Azizpour, Yifang Ban, Hamidreza Eivazi, H. Fang, F. Golzar, Iolanda Leite, Gaspar Isaac Melsión, Kevin Smith, F. Fuso Nerini, Ricardo Vinuesa:
The potential of artificial intelligence for achieving healthy and sustainable societies. CoRR abs/2202.07424 (2022) - [i18]Giuseppe Borrelli, Luca Guastoni, Hamidreza Eivazi, Philipp Schlatter, Ricardo Vinuesa:
Predicting the temporal dynamics of turbulent channels through deep learning. CoRR abs/2203.00974 (2022) - [i17]Hamidreza Eivazi, Ricardo Vinuesa:
Physics-informed deep-learning applications to experimental fluid mechanics. CoRR abs/2203.15402 (2022) - [i16]Joongoo Jeon, Juhyeong Lee, Hamidreza Eivazi, Ricardo Vinuesa, Sung Joong Kim:
Physics-Informed Transfer Learning Strategy to Accelerate Unsteady Fluid Flow Simulations. CoRR abs/2206.06817 (2022) - [i15]Soledad Le Clainche, Esteban Ferrer, Sam Gibson, Elisabeth Cross, Alessandro Parente, Ricardo Vinuesa:
Improving aircraft performance using machine learning: a review. CoRR abs/2210.11481 (2022) - [i14]Alejandro Sánchez-Roncero, Òscar Garibo-i-Ortsa, J. Alberto Conejero, Hamidreza Eivazi, Fermín Mallor, Emelie Rosenberg, Francesco Fuso Nerini, Javier García-Martínez, Ricardo Vinuesa, Sergio Hoyas:
The Sustainable Development Goals and Aerospace Engineering: A critical note through Artificial Intelligence. CoRR abs/2211.02409 (2022) - [i13]Ricardo Vinuesa, Steven L. Brunton:
Emerging trends in machine learning for computational fluid dynamics. CoRR abs/2211.15145 (2022) - 2021
- [j4]Wim Naudé, Ricardo Vinuesa:
Data deprivations, data gaps and digital divides: Lessons from the COVID-19 pandemic. Big Data Soc. 8(2): 205395172110255 (2021) - [j3]Saleh Rezaeiravesh, Ricardo Vinuesa, Philipp Schlatter:
UQit: A Python package for uncertainty quantification (UQ) in computational fluid dynamics (CFD). J. Open Source Softw. 6(60): 2871 (2021) - [j2]Raghu Raman, Ricardo Vinuesa, Prema Nedungadi:
Acquisition and User Behavior in Online Science Laboratories before and during the COVID-19 Pandemic. Multimodal Technol. Interact. 5(8): 46 (2021) - [j1]Ricardo Vinuesa, Beril Sirmaçek:
Interpretable deep-learning models to help achieve the Sustainable Development Goals. Nat. Mach. Intell. 3(11): 926 (2021) - [i12]Muhammad Shahroz, Farooq Ahmad, Muhammad Shahzad Younis, Nadeem Ahmad, Maged N. Kamel Boulos, Ricardo Vinuesa, Junaid Qadir:
COVID-19 Digital Contact Tracing Applications and Techniques: A Review Post Initial Deployments. CoRR abs/2103.01766 (2021) - [i11]Hamidreza Eivazi, Mojtaba Tahani, Philipp Schlatter, Ricardo Vinuesa:
Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations. CoRR abs/2107.10711 (2021) - [i10]Ricardo Vinuesa, Beril Sirmaçek:
Interpretable deep-learning models to help achieve the Sustainable Development Goals. CoRR abs/2108.10744 (2021) - [i9]Hamidreza Eivazi, Soledad Le Clainche Martínez, Sergio Hoyas, Ricardo Vinuesa:
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows. CoRR abs/2109.01514 (2021) - [i8]Masaki Morimoto, Kai Fukami, Romit Maulik, Ricardo Vinuesa, Koji Fukagata:
Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression. CoRR abs/2109.08248 (2021) - [i7]Ricardo Vinuesa, Steven L. Brunton:
The Potential of Machine Learning to Enhance Computational Fluid Dynamics. CoRR abs/2110.02085 (2021) - [i6]Pablo Torres, Beril Sirmaçek, Sergio Hoyas, Ricardo Vinuesa:
Aim in Climate Change and City Pollution. CoRR abs/2112.15115 (2021) - 2020
- [i5]Luca Guastoni, Prem A. Srinivasan, Hossein Azizpour, Philipp Schlatter, Ricardo Vinuesa:
On the use of recurrent neural networks for predictions of turbulent flows. CoRR abs/2002.01222 (2020) - [i4]Hamidreza Eivazi, Luca Guastoni, Philipp Schlatter, Hossein Azizpour, Ricardo Vinuesa:
Recurrent neural networks and Koopman-based frameworks for temporal predictions in turbulence. CoRR abs/2005.02762 (2020) - [i3]Ricardo Vinuesa, Andreas Theodorou, Manuela Battaglini, Virginia Dignum:
A socio-technical framework for digital contact tracing. CoRR abs/2005.08370 (2020) - [i2]David Pastor-Escuredo, Ricardo Vinuesa:
Towards and Ethical Framework in the Complex Digital Era. CoRR abs/2010.10028 (2020)
2010 – 2019
- 2019
- [c2]Anke Friederici, Wiebke Köpp, Marco Atzori, Ricardo Vinuesa, Philipp Schlatter, Tino Weinkauf:
Distributed Percolation Analysis for Turbulent Flows. LDAV 2019: 42-51 - [c1]Christian Amor, José Miguel Pérez, Philipp Schlatter, Ricardo Vinuesa, Soledad Le Clainche Martínez:
Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder. SOCO 2019: 577-586 - [i1]Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone Langhans, Max Tegmark, Francesco Fuso Nerini:
The role of artificial intelligence in achieving the Sustainable Development Goals. CoRR abs/1905.00501 (2019)
Coauthor Index
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last updated on 2024-11-05 21:01 CET by the dblp team
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