Deep learning for universal linear embeddings of nonlinear dynamics

27 December 2017

Steven L. Brunton

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

29 / 29 papers shown

Title
Accelerating Learned Image Compression Through Modeling Neural Training Dynamics Yichi Zhang Zhihao Duan Yuning Huang Fengqing Zhu 95 0 0 23 May 2025
Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning Ananyae Kumar Bhartari Vinayak Vinayak Vivek B Shenoy AI4CE 81 0 0 16 May 2025
Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era Nima Dehghani AI4CE 54 0 0 12 May 2025
Safe Navigation in Dynamic Environments Using Data-Driven Koopman Operators and Conformal Prediction Kaier Liang Guang Yang Mingyu Cai C. Vasile 81 1 0 01 Apr 2025
Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems Ruikun Zhou Yiming Meng Zhexuan Zeng Jun Liu 95 0 0 03 Dec 2024
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations Julius Aka Johannes Brunnemann Jörg Eiden Arne Speerforck Lars Mikelsons 40 0 0 14 Oct 2024
Imitation Learning with Limited Actions via Diffusion Planners and Deep Koopman Controllers Jianxin Bi Kelvin Lim Kaiqi Chen Yifei Huang Harold Soh 53 1 0 10 Oct 2024
Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs Chun-Wun Cheng Jiahao Huang Yi Zhang Guang Yang Carola-Bibiane Schonlieb Angelica I Aviles-Rivero Mamba AI4CE 106 4 0 03 Oct 2024
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices Yuka Hashimoto Tomoharu Iwata 44 0 0 03 Oct 2024
Deep Learning Alternatives of the Kolmogorov Superposition Theorem Leonardo Ferreira Guilhoto P. Perdikaris 70 7 0 02 Oct 2024
Koopman Operators in Robot Learning Lu Shi Masih Haseli Giorgos Mamakoukas Daniel Bruder Ian Abraham Todd Murphey Jorge Cortes Konstantinos Karydis AI4CE 62 7 0 08 Aug 2024
Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs Hrishikesh Viswanath Yue Chang Julius Berner Julius Berner Peter Yichen Chen Aniket Bera AI4CE 76 2 0 04 Jul 2024
Task-optimal data-driven surrogate models for eNMPC via differentiable simulation and optimization Daniel Mayfrank Na Young Ahn Alexander Mitsos Manuel Dahmen 75 2 0 21 Mar 2024
Deep Learning Based Dynamics Identification and Linearization of Orbital Problems using Koopman Theory George Nehma Madhur Tiwari M. Lingam 55 2 0 13 Mar 2024
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators Benedikt Alkin Andreas Fürst Simon Schmid Lukas Gruber Markus Holzleitner Johannes Brandstetter PINN AI4CE 98 11 0 19 Feb 2024
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder Priyam Gupta Peter J. Schmid D. Sipp T. Sayadi Georgios Rigas 47 5 0 16 Oct 2023
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems Stefan Kramer Mattia Cerrato Jannis Brugger Sašo Džeroski Ross King 44 11 0 03 May 2023
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions Ryan Lopez P. Atzberger AI4CE 46 8 0 10 Jun 2022
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 69 147 0 04 Mar 2020
Linearly-Recurrent Autoencoder Networks for Learning Dynamics Samuel E. Otto C. Rowley AI4CE 25 322 0 04 Dec 2017
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics C. Wehmeyer Frank Noé AI4CE BDL 140 358 0 30 Oct 2017
VAMPnets: Deep learning of molecular kinetics Andreas Mardt Luca Pasquali Hao Wu Frank Noé 50 542 0 16 Oct 2017
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition Naoya Takeishi Yoshinobu Kawahara Takehisa Yairi 23 367 0 12 Oct 2017
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems Enoch Yeung Soumya Kundu Nathan Oken Hodas AI4CE 17 384 0 22 Aug 2017
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 142 11,135 0 14 Mar 2016
Understanding Deep Convolutional Networks S. Mallat FAtt AI4CE 74 639 0 19 Jan 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 493 149,474 0 22 Dec 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 83 8,309 0 06 Nov 2014
A variational approach to modeling slow processes in stochastic dynamical systems Frank Noé Feliks Nuske 44 292 0 29 Nov 2012