Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling

25 February 2021

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

37 / 37 papers shown

Title
KAE: Kolmogorov-Arnold Auto-Encoder for Representation Learning Fangchen Yu Ruilizhen Hu Yidong Lin Yuqi Ma Zhenghao Huang Wenye Li 34 0 0 03 Jan 2025
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia J. C. V. Gemert Daan Brinks Nergis Tömen 38 0 0 02 Oct 2024
Generating Physical Dynamics under Priors Zihan Zhou Xiaoxue Wang Tianshu Yu DiffM AI4CE 66 0 0 01 Sep 2024
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse Problems Sojin Lee Dogyun Park Inho Kong Hyunwoo J. Kim DiffM 40 2 0 23 Jul 2024
Towards detailed and interpretable hybrid modeling of continental-scale bird migration Fiona Lippert Bart Kranstauber Patrick Forré E. E. V. Loon 39 0 0 14 Jul 2024
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration Antoine Wehenkel Juan L. Gamella Ozan Sener Jens Behrmann Guillermo Sapiro Marco Cuturi J. Jacobsen UQLM 64 8 0 14 May 2024
Physics-Enhanced Machine Learning: a position paper for dynamical systems investigations Alice Cicirello PINN AI4CE 42 9 0 08 May 2024
Physics-integrated generative modeling using attentive planar normalizing flow based variational autoencoder Sheikh Waqas Akhtar DRL 25 0 0 18 Apr 2024
The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology Juan L. Gamella Jonas Peters Peter Buhlmann 80 8 0 17 Apr 2024
Hybrid $^2$ Neural ODE Causal Modeling and an Application to Glycemic Response Bob Junyi Zou Matthew E. Levine D. Zaharieva Ramesh Johari Emily Fox 41 4 0 27 Feb 2024
Deep Learning with Physics Priors as Generalized Regularizers Frank Liu Agniva Chowdhury BDL PINN AI4CE 40 3 0 14 Dec 2023
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild Ke Alexander Wang Emily B. Fox DRL 18 0 0 06 Dec 2023
Compact and Intuitive Airfoil Parameterization Method through Physics-aware Variational Autoencoder Yu-Eop Kang Dawoon Lee K. Yee 19 0 0 18 Nov 2023
Physics-Informed Data Denoising for Real-Life Sensing Systems Xiyuan Zhang Xiaohan Fu Diyan Teng Chengyu Dong Keerthivasan Vijayakumar ... Junsheng Han Dezhi Hong Rashmi Kulkarni Jingbo Shang Rajesh K. Gupta AI4CE PINN 6 3 0 12 Nov 2023
Dream to Adapt: Meta Reinforcement Learning by Latent Context Imagination and MDP Imagination Lu Wen Songan Zhang E. Tseng Huei Peng VLM OffRL 38 6 0 11 Nov 2023
HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations Mozes Jacobs Bingni W. Brunton Steven L. Brunton J. Nathan Kutz Ryan V. Raut 11 8 0 07 Oct 2023
DPA-WNO: A gray box model for a class of stochastic mechanics problem Tushar Souvik Chakraborty DiffM 18 3 0 24 Sep 2023
Learning Hybrid Dynamics Models With Simulator-Informed Latent States K. Ensinger Sebastian Ziesche Sebastian Trimpe 31 1 0 06 Sep 2023
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 34 28 0 29 May 2023
Using VAEs to Learn Latent Variables: Observations on Applications in cryo-EM Daniel G Edelberg Roy R. Lederman CML DRL 11 6 0 13 Mar 2023
Random Grid Neural Processes for Parametric Partial Differential Equations A. Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 20 11 0 26 Jan 2023
Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies Tomoharu Iwata Yoshinobu Kawahara AI4TS AI4CE 20 0 0 26 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 27 18 0 30 Nov 2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications Zhongkai Hao Songming Liu Yichi Zhang Chengyang Ying Yao Feng Hang Su Jun Zhu PINN AI4CE 28 89 0 15 Nov 2022
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models Naoya Takeishi Alexandros Kalousis AAML 38 3 0 24 Oct 2022
Fully probabilistic deep models for forward and inverse problems in parametric PDEs A. Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 23 17 0 09 Aug 2022
Estimating counterfactual treatment outcomes over time in complex multiagent scenarios Keisuke Fujii Koh Takeuchi Atsushi Kuribayashi Naoya Takeishi Yoshinobu Kawahara K. Takeda CML 27 14 0 04 Jun 2022
Neural Implicit Representations for Physical Parameter Inference from a Single Video Florian Hofherr Lukas Koestler Florian Bernard Daniel Cremers AI4CE 37 9 0 29 Apr 2022
Robust Hybrid Learning With Expert Augmentation Antoine Wehenkel Jens Behrmann Hsiang Hsu Guillermo Sapiro Gilles Louppe and J. Jacobsen 26 8 0 08 Feb 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 28 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 42 68 0 14 Sep 2021
Disentangled Generative Models for Robust Prediction of System Dynamics Stathi Fotiadis Mario Lino Valencia Shunlong Hu Stef Garasto C. Cantwell Anil Anthony Bharath DRL OOD CML 8 9 0 26 Aug 2021
Physics guided machine learning using simplified theories Suraj Pawar Omer San Burak Aksoylu Adil Rasheed T. Kvamsdal PINN AI4CE 100 106 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 183 759 0 13 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction Vincent Le Guen Nicolas Thome AI4CE PINN 89 288 0 03 Mar 2020
Hybrid Physical-Deep Learning Model for Astronomical Inverse Problems F. Lanusse Peter Melchior Fred Moolekamp BDL 27 12 0 09 Dec 2019