39 citations · 39 across the 4 of their papers we have counts for
3 papers · 1 filter
Variational Augmented Invertible Koopman Autoencoder for probabilistic time series forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +3
Neural Koopman autoencoder models have been shown to successfully build a latent embedding with linear dynamics for arbitrary dynamical systems, enabling strong performance in long…
Multiphysics discovery with moving boundaries using Ensemble SINDy and Peridynamic Differential Operator
A. C. Bekar, E. Haghighat, E. Madenci
This study proposes a novel framework for learning the underlying physics of phenomena with moving boundaries. The proposed approach combines Ensemble SINDy and Peridynamic Differe…
An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic differential operator
A. Mavi, A. C. Bekar, E. Haghighat +1
This study presents a novel unsupervised convolutional Neural Network (NN) architecture with nonlocal interactions for solving Partial Differential Equations (PDEs). The nonlocal P…