152 citations · 285 across the 20 of their papers we have counts for
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Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification
Thomas Beckers, Tom Z. Jiahao, George J. Pappas
Switching physical systems are ubiquitous in modern control applications, for instance, locomotion behavior of robots and animals, power converters with switches and diodes. The dy…
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior
Thomas Beckers, Jacob Seidman, Paris Perdikaris +1
Data-driven approaches achieve remarkable results for the modeling of complex dynamics based on collected data. However, these models often neglect basic physical principles which…
Physics-enhanced Gaussian Process Variational Autoencoder
Thomas Beckers, Qirui Wu, George J. Pappas
Variational autoencoders allow to learn a lower-dimensional latent space based on high-dimensional input/output data. Using video clips as input data, the encoder may be used to de…