Physics-Integrated Variational Autoencoders for Robust and Interpretable
Generative Modeling

Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling

25 February 2021

Alexandros Kalousis

Papers citing "Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling"

14 / 14 papers shown

Title
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia J. C. V. Gemert Daan Brinks Nergis Tömen 31 0 0 02 Oct 2024
Generating Physical Dynamics under Priors Zihan Zhou Xiaoxue Wang Tianshu Yu DiffM AI4CE 50 0 0 01 Sep 2024
Learning Hybrid Dynamics Models With Simulator-Informed Latent States K. Ensinger Sebastian Ziesche Sebastian Trimpe 22 1 0 06 Sep 2023
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 30 27 0 29 May 2023
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 12 17 0 30 Nov 2022
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models Naoya Takeishi Alexandros Kalousis AAML 10 3 0 24 Oct 2022
Neural Implicit Representations for Physical Parameter Inference from a Single Video Florian Hofherr Lukas Koestler Florian Bernard Daniel Cremers AI4CE 27 9 0 29 Apr 2022
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling Gianluigi Silvestri Emily Fertig David A. Moore L. Ambrogioni BDL TPM AI4CE 23 3 0 12 Oct 2021
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 32 67 0 14 Sep 2021
Physics guided machine learning using simplified theories Suraj Pawar Omer San Burak Aksoylu Adil Rasheed T. Kvamsdal PINN AI4CE 92 87 0 18 Dec 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 170 755 0 13 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 121 419 0 10 Mar 2020
Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction Vincent Le Guen Nicolas Thome AI4CE PINN 78 287 0 03 Mar 2020
Hybrid Physical-Deep Learning Model for Astronomical Inverse Problems F. Lanusse Peter Melchior Fred Moolekamp BDL 14 12 0 09 Dec 2019