Distributed Percolation Analysis for Turbulent Flows. - Anke Friederici; Wiebke Köpp; Marco Atzori; Ricardo Vinuesa; Philipp Schlatter; Tino Weinkauf (LDAV, 2019)

Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder. - Christian Amor; José Miguel Pérez; Philipp Schlatter; Ricardo Vinuesa; Soledad Le Clainche Martínez (SOCO, 2019)

The role of artificial intelligence in achieving the Sustainable Development Goals. - Ricardo Vinuesa; Hossein Azizpour; Iolanda Leite; Madeline Balaam; Virginia Dignum; Sami Domisch; Anna Felländer; Simone Langhans; Max Tegmark; Francesco Fuso Nerini (CoRR, 2019)

On the use of recurrent neural networks for predictions of turbulent flows. - Luca Guastoni; Prem A. Srinivasan; Hossein Azizpour; Philipp Schlatter; Ricardo Vinuesa (CoRR, 2020)

Recurrent neural networks and Koopman-based frameworks for temporal predictions in turbulence. - Hamidreza Eivazi; Luca Guastoni; Philipp Schlatter; Hossein Azizpour; Ricardo Vinuesa (CoRR, 2020)

A socio-technical framework for digital contact tracing. - Ricardo Vinuesa; Andreas Theodorou; Manuela Battaglini; Virginia Dignum (CoRR, 2020)

Towards and Ethical Framework in the Complex Digital Era. - David Pastor-Escuredo; Ricardo Vinuesa (CoRR, 2020)

COVID-19 Digital Contact Tracing Applications and Techniques: A Review Post Initial Deployments. - Muhammad Shahroz; Farooq Ahmad; Muhammad Shahzad Younis; Nadeem Ahmad; Maged N. Kamel Boulos; Ricardo Vinuesa; Junaid Qadir 001 (CoRR, 2021)

Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations. - Hamidreza Eivazi; Mojtaba Tahani; Philipp Schlatter; Ricardo Vinuesa (CoRR, 2021)

Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression. - Masaki Morimoto; Kai Fukami; Romit Maulik; Ricardo Vinuesa; Koji Fukagata (CoRR, 2021)

The Potential of Machine Learning to Enhance Computational Fluid Dynamics. - Ricardo Vinuesa; Steven L. Brunton (CoRR, 2021)

Aim in Climate Change and City Pollution. - Pablo Torres; Beril Sirmaçek; Sergio Hoyas; Ricardo Vinuesa (CoRR, 2021)

UQit: A Python package for uncertainty quantification (UQ) in computational fluid dynamics (CFD). - Saleh Rezaeiravesh; Ricardo Vinuesa; Philipp Schlatter (J. Open Source Softw., 2021)

Acquisition and User Behavior in Online Science Laboratories before and during the COVID-19 Pandemic. - Raghu Raman; Ricardo Vinuesa; Prema Nedungadi (Multimodal Technol. Interact., 2021)

Interpretable deep-learning models to help achieve the Sustainable Development Goals. - Ricardo Vinuesa; Beril Sirmaçek (Nat. Mach. Intell., 2021)

Data deprivations, data gaps and digital divides: Lessons from the COVID-19 pandemic. - Wim Naudé; Ricardo Vinuesa (Big Data Soc., 2021)

Understanding the Bibliometric Patterns of Publications in IEEE Access. - Raghu Raman; Prashasti Singh; Vivek Kumar Singh 001; Ricardo Vinuesa; Prema Nedungadi (IEEE Access, 2022)

The potential of artificial intelligence for achieving healthy and sustainable societies. - Beril Sirmaçek; S. Gupta; Fermín Mallor; Hossein Azizpour; Yifang Ban; Hamidreza Eivazi; Heng Fang; F. Golzar; Iolanda Leite; Gaspar Isaac Melsión; Kevin Smith 001; Francesco Fuso Nerini; et al. (CoRR, 2022)

Predicting the temporal dynamics of turbulent channels through deep learning. - Giuseppe Borrelli; Luca Guastoni; Hamidreza Eivazi; Philipp Schlatter; Ricardo Vinuesa (CoRR, 2022)

Physics-informed deep-learning applications to experimental fluid mechanics. - Hamidreza Eivazi; Ricardo Vinuesa (CoRR, 2022)

Physics-Informed Transfer Learning Strategy to Accelerate Unsteady Fluid Flow Simulations. - Joongoo Jeon; Juhyeong Lee; Hamidreza Eivazi; Ricardo Vinuesa; Sung Joong Kim (CoRR, 2022)

Improving aircraft performance using machine learning: a review. - Soledad Le Clainche; Esteban Ferrer 001; Sam Gibson; Elisabeth Cross; Alessandro Parente; Ricardo Vinuesa (CoRR, 2022)

The Sustainable Development Goals and Aerospace Engineering: A critical note through Artificial Intelligence. - 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 (CoRR, 2022)

Emerging Trends in Machine Learning for Computational Fluid Dynamics. - Ricardo Vinuesa; Steven L. Brunton (Comput. Sci. Eng., 2022)

Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows. - Hamidreza Eivazi; Soledad Le Clainche; Sergio Hoyas; Ricardo Vinuesa (Expert Syst. Appl., 2022)

Modeling the Turbulent Wake Behind a Wall-Mounted Square Cylinder. - Christian Amor; José Miguel Pérez; Philipp Schlatter; Ricardo Vinuesa; Soledad Le Clainche (Log. J. IGPL, 2022)

Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula. - Rana Tallal Javed; Osama Nasir; Melania Borit; Loïs Vanhée; Elias Zea; Shivam Gupta 005; Ricardo Vinuesa; Junaid Qadir 001 (J. Artif. Intell. Res., 2022)

Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems. - Yuki Morita; Saleh Rezaeiravesh; N. Tabatabaei; Ricardo Vinuesa; Koji Fukagata; Philipp Schlatter (J. Comput. Phys., 2022)

An uncertainty-quantification framework for assessing accuracy, sensitivity, and robustness in computational fluid dynamics. - Saleh Rezaeiravesh; Ricardo Vinuesa; Philipp Schlatter (J. Comput. Sci., 2022)

Enhancing computational fluid dynamics with machine learning. - Ricardo Vinuesa; Steven L. Brunton (Nat. Comput. Sci., 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]. - 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; et al. (IEEE Robotics Autom. Mag., 2022)

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection. - Dmytro Mamchur; Janis Peksa; Soledad Le Clainche; Ricardo Vinuesa (Sensors, 2022)

Innovative software systems for managing the impact of the COVID-19 pandemic. - Sukhpal Singh Gill; Ricardo Vinuesa; Venki Balasubramanian; Soumya K. Ghosh 001 (Softw. Pract. Exp., 2022)

In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst. - 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; et al. (J. Supercomput., 2022)

Get Out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula (Extended Abstract). - Rana Tallal Javed; Osama Nasir; Melania Borit; Loïs Vanhée; Elias Zea; Shivam Gupta 005; Ricardo Vinuesa; Junaid Qadir 001 (IJCAI, 2023)

Explaining wall-bounded turbulence through deep learning. - Andres Cremades; Sergio Hoyas; Pedro Quintero; Martin Lellep; Moritz Linkmann; Ricardo Vinuesa (CoRR, 2023)

The transformative potential of machine learning for experiments in fluid mechanics. - Ricardo Vinuesa; Steven L. Brunton; Beverley J. McKeon (CoRR, 2023)

Closing the gap between research and projects in climate change innovation in Europe. - Francesca Larosa; Jaroslav Mysiak; Marco Molinari; Panagiotis Varelas; Haluk Akay; Will McDowall; Catalina Spadaru; Francesco Fuso Nerini; Ricardo Vinuesa (CoRR, 2023)

Effective control of two-dimensional Rayleigh-Bénard convection: invariant multi-agent reinforcement learning is all you need. - Colin Vignon; Jean Rabault; Joel Vasanth; Francisco Alcántara-Ávila; Mikael Mortensen; Ricardo Vinuesa (CoRR, 2023)

β-Variational autoencoders and transformers for reduced-order modelling of fluid flows. - Alberto Solera-Rico; Carlos Sanmiguel Vila; Miguel A. Gómez; Yuning Wang; Abdulrahman Almashjary; Scott T. M. Dawson; Ricardo Vinuesa (CoRR, 2023)

Discovering Causal Relations and Equations from Data. - Gustau Camps-Valls; Andreas Gerhardus; Urmi Ninad; Gherardo Varando; Georg Martius; Emili Balaguer-Ballester; Ricardo Vinuesa; Emiliano Diaz; Laure Zanna; Jakob Runge (CoRR, 2023)

Easy attention: A simple self-attention mechanism for Transformers. - Marcial Sanchis-Agudo; Yuning Wang; Karthik Duraisamy; Ricardo Vinuesa (CoRR, 2023)

Active flow control for three-dimensional cylinders through deep reinforcement learning. - Pol Suárez; Francisco Alcántara-Ávila; Arnau Miró; Jean Rabault; Bernat Font; Oriol Lehmkuhl; Ricardo Vinuesa (CoRR, 2023)

From fear to action: AI governance and opportunities for all. - Kevin Baum 001; Joanna Bryson; Frank Dignum; Virginia Dignum; Marko Grobelnik; Holger H. Hoos; Morten Irgens; Paul Lukowicz; Catelijne Muller; Francesca Rossi 001; John Shawe-Taylor; Andreas Theodorou; et al. (Frontiers Comput. Sci., 2023)

Higher-order dynamic mode decomposition on-the-fly: A low-order algorithm for complex fluid flows. - Christian Amor; Philipp Schlatter; Ricardo Vinuesa; Soledad Le Clainche (J. Comput. Phys., 2023)

Improving the Learning of Mechanics Through Augmented Reality. - Clarissa Hedenqvist; Mario Romero; Ricardo Vinuesa (Technol. Knowl. Learn., 2023)

Beyond the Buzz: Strategic Paths for Enabling Useful NISQ Applications. - Pratibha Raghupati Hegde; Oleksandr Kyriienko; Hermanni Heimonen; Panagiotis Tolias; Gilbert Netzer; Panagiotis Kl. Barkoutsos; Ricardo Vinuesa; Ivy Peng; Stefano Markidis (CF, 2024)

Auto-tuning Multi-GPU High-Fidelity Numerical Simulations for Urban Air Mobility. - Konstantina Koliogeorgi; George Anagnostopoulos; Gerardo Zampino; Marcial Sanchis; Ricardo Vinuesa; Sotirios Xydis (DATE, 2024)

AI in Space for Scientific Missions: Strategies for Minimizing Neural-Network Model Upload. - Jonah Ekelund; Ricardo Vinuesa; Yuri V. Khotyaintsev; Pierre Henri; Gian Luca Delzanno; Stefano Markidis (e-Science, 2024)

Indirectly Parameterized Concrete Autoencoders. - Alfred Nilsson; Klas Wijk; Sai Bharath Chandra Gutha; Erik Englesson; Alexandra Hotti; Carlo Saccardi; Oskar Kviman; Jens Lagergren; Ricardo Vinuesa; Hossein Azizpour (ICML, 2024)

Opportunities for machine learning in scientific discovery. - 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 (CoRR, 2024)

Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction. - Sunwoong Yang; Ricardo Vinuesa; Namwoo Kang (CoRR, 2024)

Revisiting Score Function Estimators for k-Subset Sampling. - Klas Wijk; Ricardo Vinuesa; Hossein Azizpour (CoRR, 2024)

Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality. - Joogoo Jeon; Jean Rabault; Joel Vasanth; Francisco Alcántara-Ávila; Shilaj Baral; Ricardo Vinuesa (CoRR, 2024)

Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection. - Joel Vasanth; Jean Rabault; Francisco Alcántara-Ávila; Mikael Mortensen; Ricardo Vinuesa (CoRR, 2024)

Additive-feature-attribution methods: a review on explainable artificial intelligence for fluid dynamics and heat transfer. - Andres Cremades; Sergio Hoyas; Ricardo Vinuesa (CoRR, 2024)

Transformer-Based Fault-Tolerant Control for Fixed-Wing UAVs Using Knowledge Distillation and In-Context Adaptation. - Francisco Giral; Ignacio Gómez; Ricardo Vinuesa; Soledad Le Clainche (CoRR, 2024)

Towards Robust Spatio-Temporal Auto-Regressive Prediction: Adams-Bashforth Time Integration with Adaptive Multi-Step Rollout. - Sunwoong Yang; Ricardo Vinuesa; Namwoo Kang (CoRR, 2024)

Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks. - Aniel Jardines; Hamidreza Eivazi; Elias Zea; Javier García-Heras; Juan Simarro; Evelyn Otero; Manuel Soler; Ricardo Vinuesa (Expert Syst. Appl., 2024)

POSTER: Performance Portability in GPU-Accelerated Spectral Finite Element Fluid Simulations: A Cross-layer Exploration Approach. - Panagiotis-Eleftherios Eleftherakis; George Anagnostopoulos; Anastassis Kapetanakis; Mohammad Umair; Jean-Yves Vet; Konstantinos Iliakis; Jonathan Vincent; Jing Gong; Ricardo Vinuesa; Sotirios Xydis (CF, 2025)

SFESS: Score Function Estimators for k-Subset Sampling. - Klas Wijk; Ricardo Vinuesa; Hossein Azizpour (ICLR, 2025)

Inverse Problems with Diffusion Models: A MAP Estimation Perspective. - Sai Bharath Chandra Gutha; Ricardo Vinuesa; Hossein Azizpour (WACV, 2025)

Navigation in a simplified urban flow through deep reinforcement learning. - Federica Tonti; Jean Rabault; Ricardo Vinuesa (J. Comput. Phys., 2025)

Large language models in climate and sustainability policy: limits and opportunities. - Francesca Larosa; Sergio Hoyas; H. Alberto Conejero; Javier García-Martínez; Francesco Fuso Nerini; Ricardo Vinuesa (CoRR, 2025)

Deep-reinforcement-learning-based separation control in a two-dimensional airfoil. - Xavier Garcia; Arnau Miró; Pol Suárez; Francisco Alcántara-Ávila; Jean Rabault; Bernat Font; Oriol Lehmkuhl; Ricardo Vinuesa (CoRR, 2025)

Regional climate projections using a deep-learning-based model-ranking and downscaling framework: Application to European climate zones. - Parthiban Loganathan; Elias Zea; Ricardo Vinuesa; Evelyn Otero (CoRR, 2025)

Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments. - Abhijeet Vishwasrao; Sai Bharath Chandra Gutha; Andres Cremades; Klas Wijk; Aakash Patil; Catherine Gorle; Beverley J. McKeon; Hossein Azizpour; Ricardo Vinuesa (CoRR, 2025)

Evaluating Visual Mathematics in Multimodal LLMs: A Multilingual Benchmark Based on the Kangaroo Tests. - Arnau Igualde Sáez; Lamyae Rhomrasi; Yusef Ahsini; Ricardo Vinuesa; Sergio Hoyas; José Pedro García-Sabater; Marius J. Fullana i Alfonso; J. Alberto Conejero (CoRR, 2025)