Interpretable deep-learning models to help achieve the Sustainable
Development Goals

Interpretable deep-learning models to help achieve the Sustainable Development Goals

24 August 2021

Ricardo Vinuesa

Papers citing "Interpretable deep-learning models to help achieve the Sustainable Development Goals"

18 / 18 papers shown

Title
iFuzzyTL: Interpretable Fuzzy Transfer Learning for SSVEP BCI System Xiaowei Jiang Beining Cao Liang Ou Yu-Cheng Chang T. Do Chin-Teng Lin 36 2 0 16 Oct 2024
Additive-feature-attribution methods: a review on explainable artificial intelligence for fluid dynamics and heat transfer Andres Cremades S. Hoyas Ricardo Vinuesa FAtt 29 9 0 18 Sep 2024
Domain adaptation in small-scale and heterogeneous biological datasets Seyedmehdi Orouji Martin C. Liu T. Korem Megan A. K. Peters 21 7 0 29 May 2024
Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental Data Yaxin Mo Tullio Traverso Luca Magri AI4CE 23 4 0 25 Apr 2024
End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning Md Nasim Anter El-Azab Xinghang Zhang Yexiang Xue 14 0 0 13 Sep 2023
Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data G. Lorenzo Syed Rakin Ahmed D. Hormuth Brenna Vaughn Jayashree Kalpathy-Cramer Luis Solorio T. Yankeelov H. Gómez AI4CE 37 13 0 28 Aug 2023
Towards credible visual model interpretation with path attribution Naveed Akhtar Muhammad A. A. K. Jalwana FAtt 22 5 0 23 May 2023
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 40 73 0 21 May 2023
Learning and Reasoning Multifaceted and Longitudinal Data for Poverty Estimates and Livelihood Capabilities of Lagged Regions in Rural India Atharva Kulkarni Raya Das R. Srivastava Tanmoy Chakraborty 9 2 0 27 Apr 2023
Rethinking interpretation: Input-agnostic saliency mapping of deep visual classifiers Naveed Akhtar M. Jalwana FAtt AAML 19 7 0 31 Mar 2023
The transformative potential of machine learning for experiments in fluid mechanics Ricardo Vinuesa Steven L. Brunton B. McKeon AI4CE 35 68 0 28 Mar 2023
Improving aircraft performance using machine learning: a review S. L. Clainche E. Ferrer Sam Gibson Elisabeth Cross A. Parente Ricardo Vinuesa AI4CE 36 93 0 20 Oct 2022
Physics-informed deep-learning applications to experimental fluid mechanics Hamidreza Eivazi Yuning Wang Ricardo Vinuesa PINN AI4CE 21 44 0 29 Mar 2022
Predicting the temporal dynamics of turbulent channels through deep learning Giuseppe Borrelli L. Guastoni Hamidreza Eivazi P. Schlatter Ricardo Vinuesa AI4TS 22 17 0 02 Mar 2022
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 121 355 0 05 Oct 2021
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows Hamidreza Eivazi S. L. C. Martínez S. Hoyas Ricardo Vinuesa 33 92 0 03 Sep 2021
Remote sensing and AI for building climate adaptation applications B. Sirmaçek Ricardo Vinuesa AI4CE 23 33 0 06 Jul 2021
Towards an Ethical Framework in the Complex Digital Era D. Pastor-Escuredo Ricardo Vinuesa 28 12 0 19 Oct 2020