Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Visualizing Data using t-SNE

Laurens van der Maaten, Geoffrey E. Hinton · Journal of Machine Learning Research · 2008 · 35.7K citations

Engineering, Data Visualization, Data Exploration +16

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 14.4K citations · Full text

Engineering, Pde-constrained Optimization, Deep Learning Framework +6

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

Lantao Yu, Weinan Zhang, Jun Wang et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2017 · 2.3K citations · Full text

Artificial Intelligence, Monte Carlo Search, Engineering +12

Physics-informed neural networks for high-speed flows

Zhiping Mao, Ameya D. Jagtap, George Em Karniadakis · Computer Methods in Applied Mechanics and Engineering · 2019 · 1.1K citations

Unsteady Flow, Engineering, Physic Aware Machine Learning +4

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

Xiaowei Jin, Shengze Cai, Hui Li et al. · Journal of Computational Physics · 2020 · 1.1K citations · Full text

Compressible Flow, Engineering, Incompressible Flow +9