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Deep learning for universal linear embeddings of nonlinear dynamics

27 December 2017

Bethany Lusch

J. Nathan Kutz

Steven L. Brunton

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Papers citing "Deep learning for universal linear embeddings of nonlinear dynamics"

50 / 411 papers shown

Title
Simulation-Based Parallel Training Lucas Meyer Alejandro Ribés Bruno Raffin AI4CE 70 2 0 08 Nov 2022
WeakIdent: Weak formulation for Identifying Differential Equations using Narrow-fit and Trimming Mengyi Tang Wenjing Liao R. Kuske S. Kang 55 19 0 06 Nov 2022
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning Di Luo Jiayu Shen Rumen Dangovski Marin Soljacic 79 5 0 02 Nov 2022
Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning P. Goyal P. Benner 74 12 0 01 Nov 2022
Learned Lifted Linearization Applied to Unstable Dynamic Systems Enabled by Koopman Direct Encoding Jerry Ng H. Asada 75 2 0 24 Oct 2022
Bridging the Gap between Artificial Intelligence and Artificial General Intelligence: A Ten Commandment Framework for Human-Like Intelligence Ananta Nair F. Kashani 69 2 0 17 Oct 2022
Flipped Classroom: Effective Teaching for Time Series Forecasting P. Teutsch Patrick Mäder AI4TS 67 8 0 17 Oct 2022
Deep Koopman with Control: Spectral Analysis of Soft Robot Dynamics N. Komeno B. Michael Katharina Küchler Edgar Anarossi Takamitsu Matsubara 60 9 0 14 Oct 2022
Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts Rui Wang Yihe Dong Sercan O. Arik Rose Yu AI4TS 109 28 0 07 Oct 2022
Accelerate Reinforcement Learning with PID Controllers in the Pendulum Simulations Liping Bai 23 0 0 03 Oct 2022
Phy-Taylor: Physics-Model-Based Deep Neural Networks Y. Mao L. Sha Huajie Shao Yuliang Gu Qixin Wang Tarek Abdelzaher PINN AI4CE 101 1 0 27 Sep 2022
Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories Samuel E. Otto Sebastian Peitz C. Rowley 84 19 0 20 Sep 2022
The mpEDMD Algorithm for Data-Driven Computations of Measure-Preserving Dynamical Systems Matthew J. Colbrook 81 34 0 06 Sep 2022
Discovering Conservation Laws using Optimal Transport and Manifold Learning Peter Y. Lu Rumen Dangovski M. Soljavcić 82 18 0 31 Aug 2022
Data-driven Predictive Tracking Control based on Koopman Operators Ye Wang Yujia Yang Ye Pu Chris Manzie 39 10 0 25 Aug 2022
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks Zhi-Ling Dong Pawel Polak PINN 96 1 0 18 Aug 2022
Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces Tomoharu Iwata Yoshinobu Kawahara 46 3 0 16 Aug 2022
RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances Baolin Li Rohan Basu Roy Tirthak Patel V. Gadepally K. Gettings Devesh Tiwari 55 25 0 23 Jul 2022
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures Zhilu Lai Wei Liu Xudong Jian Kiran Bacsa Limin Sun Eleni Chatzi AI4CE 67 23 0 16 Jul 2022
Heterogeneous mixtures of dictionary functions to approximate subspace invariance in Koopman operators Charles A. Johnson Shara Balakrishnan Enoch Yeung 26 2 0 27 Jun 2022
Learning neural state-space models: do we need a state estimator? Marco Forgione Manas Mejari Dario Piga 47 12 0 26 Jun 2022
Computational Complexity Evaluation of Neural Network Applications in Signal Processing Pedro J. Freire S. Srivallapanondh A. Napoli Jaroslaw E. Prilepsky S. Turitsyn 90 1 0 24 Jun 2022
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions Ryan Lopez P. Atzberger AI4CE 119 8 0 10 Jun 2022
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations Julius Berner Jinxu Xiang D. Cho Yue Chang G. Pershing H. Maia Maurizio M. Chiaramonte Kevin Carlberg E. Grinspun AI4CE 123 44 0 06 Jun 2022
Data-Driven Linear Koopman Embedding for Networked Systems: Model-Predictive Grid Control Ramij-Raja Hossain Rahmat Adesunkanmi Ratnesh Kumar 47 6 0 02 Jun 2022
Learning Sparse Nonlinear Dynamics via Mixed-Integer Optimization Dimitris Bertsimas Wes Gurnee AI4CE 84 46 0 01 Jun 2022
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces Vladimir Kostic P. Novelli Andreas Maurer C. Ciliberto Lorenzo Rosasco Massimiliano Pontil 78 62 0 27 May 2022
Transformer for Partial Differential Equations' Operator Learning Zijie Li Kazem Meidani A. Farimani 117 172 0 26 May 2022
Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs Mona Buisson-Fenet V. Morgenthaler Sebastian Trimpe F. D. Meglio 83 6 0 25 May 2022
Neural ODEs with Irregular and Noisy Data P. Goyal P. Benner 56 4 0 19 May 2022
Deep Learning of Chaotic Systems from Partially-Observed Data V. Churchill D. Xiu 92 13 0 12 May 2022
Regression-based projection for learning Mori-Zwanzig operators Yen Ting Lin Yifeng Tian D. Perez Daniel Livescu 77 11 0 10 May 2022
LPC-AD: Fast and Accurate Multivariate Time Series Anomaly Detection via Latent Predictive Coding Zhi Qi Hong Xie Ye Li Jian Tan Feifei Li John C. S. Lui AI4TS 59 2 0 05 May 2022
Learning Reduced Nonlinear State-Space Models: an Output-Error Based Canonical Approach Steeven Janny Quentin Possamaï L. Bako Madiha Nadri Wolf Christian Wolf 71 2 0 19 Apr 2022
Assessment of convolutional recurrent autoencoder network for learning wave propagation Wrik Mallik R. Jaiman J. Jelovica BDL 24 1 0 12 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 122 59 0 31 Mar 2022
Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems Alec J. Linot J. Burby Q. Tang Prasanna Balaprakash M. Graham R. Maulik AI4TS 75 74 0 29 Mar 2022
Can A Neural Network Hear the Shape of A Drum? Yueqi Zhao M. Fogler 46 1 0 14 Mar 2022
Predicting the temporal dynamics of turbulent channels through deep learning Giuseppe Borrelli L. Guastoni Hamidreza Eivazi P. Schlatter Ricardo Vinuesa AI4TS 82 18 0 02 Mar 2022
Direct data-driven forecast of local turbulent heat flux in Rayleigh-Bénard convection S. Pandey P. Teutsch Patrick Mäder J. Schumacher 115 33 0 26 Feb 2022
Deep Koopman Operator with Control for Nonlinear Systems Hao-bin Shi Max Meng 73 79 0 16 Feb 2022
Learned Turbulence Modelling with Differentiable Fluid Solvers: Physics-based Loss-functions and Optimisation Horizons Bjorn List Li-Wei Chen Nils Thuerey 80 57 0 14 Feb 2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning Said Ouala Steven L. Brunton A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet PINN AI4TS AI4CE 71 10 0 11 Feb 2022
Rediscovering orbital mechanics with machine learning Pablo Lemos N. Jeffrey M. Cranmer S. Ho Peter W. Battaglia PINN AI4CE 84 92 0 04 Feb 2022
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space Steeven Janny Fabien Baradel Natalia Neverova M. Nadri Greg Mori Christian Wolf CML 91 15 0 01 Feb 2022
Predicting Physics in Mesh-reduced Space with Temporal Attention Xu Han Han Gao Tobias Pfaff Jian-Xun Wang Liping Liu AI4CE 91 83 0 22 Jan 2022
Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders Joseph Bakarji Kathleen P. Champion J. Nathan Kutz Steven L. Brunton 111 86 0 13 Jan 2022
Neural Koopman Lyapunov Control Vrushabh Zinage E. Bakolas 57 28 0 13 Jan 2022
Data-Driven Modeling and Prediction of Non-Linearizable Dynamics via Spectral Submanifolds Mattia Cenedese Joar Axås Bastian Bäuerlein Kerstin Avila George Haller 84 127 0 13 Jan 2022
Augmenting astrophysical scaling relations with machine learning: application to reducing the Sunyaev-Zeldovich flux-mass scatter D. Wadekar L. Thiele F. Villaescusa-Navarro J. Hill M. Cranmer D. Spergel N. Battaglia D. Anglés-Alcázar L. Hernquist S. Ho 114 12 0 04 Jan 2022