Deep Learning of Vortex Induced Vibrations

26 August 2018

Papers citing "Deep Learning of Vortex Induced Vibrations"

32 / 32 papers shown

Title
Plane-Wave Decomposition and Randomised Training; a Novel Path to Generalised PINNs for SHM Rory Clements James Ellis Geoff Hassall Simon Horsley Gavin Tabor 58 0 0 31 Mar 2025
PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction Han Wan Qi Wang Hao Sun Hao Sun AI4CE 57 1 0 13 Mar 2025
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning Nilo Schwencke Cyril Furtlehner 64 1 0 14 Dec 2024
Regression Trees Know Calculus Nathan Wycoff 31 0 0 22 May 2024
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 11 0 08 Aug 2023
Efficient Error Certification for Physics-Informed Neural Networks Francisco Eiras Adel Bibi Rudy Bunel Krishnamurthy Dvijotham Philip H. S. Torr M. P. Kumar PINN 26 1 0 17 May 2023
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Xuan Di Rongye Shi Zhaobin Mo Yongjie Fu PINN AI4TS AI4CE 26 28 0 03 Mar 2023
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 24 17 0 27 Oct 2022
How important are activation functions in regression and classification? A survey, performance comparison, and future directions Ameya Dilip Jagtap George Karniadakis AI4CE 31 71 0 06 Sep 2022
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies Adam Thelen Xiaoge Zhang Olga Fink Yan Lu Sayan Ghosh B. Youn Michael D. Todd S. Mahadevan Chao Hu Zhen Hu SyDa AI4CE 27 187 0 26 Aug 2022
Flow Completion Network: Inferring the Fluid Dynamics from Incomplete Flow Information using Graph Neural Networks Xiaodong He Yinan Wang Juan Li GNN 17 19 0 10 May 2022
$Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations$ Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations Ling Guo Hao Wu Xiao-Jun Yu Tao Zhou PINN AI4CE 21 58 0 16 Mar 2022
Physics-informed neural networks for inverse problems in supersonic flows Ameya Dilip Jagtap Zhiping Mao Nikolaus Adams George Karniadakis PINN 18 201 0 23 Feb 2022
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 25 152 0 09 Oct 2021
Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion S. Basir Inanc Senocak PINN AI4CE 34 68 0 30 Sep 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 18 76 0 20 Sep 2021
PCNN: A physics-constrained neural network for multiphase flows Haoyang Zheng Ziyang Huang Guang Lin PINN 19 8 0 18 Sep 2021
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks S. Maddu D. Sturm Christian L. Müller I. Sbalzarini AI4CE 21 81 0 02 Jul 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 71 222 0 26 Apr 2021
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning R. Sepasdar Anuj Karpatne Maryam Shakiba AI4CE 21 58 0 09 Apr 2021
Can Transfer Neuroevolution Tractably Solve Your Differential Equations? Jian Cheng Wong Abhishek Gupta Yew-Soon Ong 28 21 0 06 Jan 2021
A Physics-Informed Deep Learning Paradigm for Car-Following Models Zhaobin Mo Xuan Di Rongye Shi PINN AI4CE 22 131 0 24 Dec 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sifan Wang Xinling Yu P. Perdikaris 33 877 0 28 Jul 2020
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao Sun Yang Liu PINN AI4CE 17 222 0 10 Jun 2020
Multi-fidelity Generative Deep Learning Turbulent Flows N. Geneva N. Zabaras AI4CE 16 44 0 08 Jun 2020
Deep learning of free boundary and Stefan problems Sifan Wang P. Perdikaris 21 80 0 04 Jun 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 54 123 0 17 May 2020
Data-driven Flood Emulation: Speeding up Urban Flood Predictions by Deep Convolutional Neural Networks Zifeng Guo J. Leitão N. Simões V. Moosavi AI4CE 17 117 0 17 Apr 2020
Variational Physics-Informed Neural Networks For Solving Partial Differential Equations E. Kharazmi Z. Zhang George Karniadakis 16 236 0 27 Nov 2019
Physics-Informed Echo State Networks for Chaotic Systems Forecasting N. Doan W. Polifke Luca Magri 6 39 0 09 Apr 2019
Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis M. A. Nabian Hadi Meidani PINN AI4CE 19 57 0 11 Oct 2018
General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning Shiyin Wei Xiaowei Jin Hui Li AI4CE 30 39 0 13 May 2018