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Linearly-Recurrent Autoencoder Networks for Learning Dynamics

4 December 2017

Papers citing "Linearly-Recurrent Autoencoder Networks for Learning Dynamics"

50 / 124 papers shown

Title
Intrinsic Dimensionality of Fermi-Pasta-Ulam-Tsingou High-Dimensional Trajectories Through Manifold Learning: A Linear Approach Gionni Marchetti 41 0 0 01 Jul 2025
T-SHRED: Symbolic Regression for Regularization and Model Discovery with Transformer Shallow Recurrent Decoders Alexey Yermakov David Zoro Mars Liyao Gao J. Nathan Kutz 25 0 0 18 Jun 2025
Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison Jan C. Schulze Alexander Mitsos 22 0 0 15 Jun 2025
Automated Manifold Learning for Reduced Order Modeling Imran Nasim Melanie Weber AI4CE 61 0 0 02 Jun 2025
One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling Nimrod Berman Ilan Naiman Moshe Eliasof Hedi Zisling Omri Azencot DiffM OffRL 91 0 0 19 May 2025
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics Christoph Jürgen Hemmer Daniel Durstewitz AI4TS SyDa AI4CE 297 1 0 19 May 2025
Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders Fynn Fromme Christine Allen-Blanchette Hans Harder Sebastian Peitz AI4CE SyDa 92 0 0 19 May 2025
Compression, Regularity, Randomness and Emergent Structure: Rethinking Physical Complexity in the Data-Driven Era Nima Dehghani AI4CE 110 0 0 12 May 2025
Augmented Invertible Koopman Autoencoder for long-term time series forecasting Anthony Frion Lucas Drumetz M. Dalla Mura Guillaume Tochon Abdeldjalil Aissa El Bey AI4TS 81 0 0 17 Mar 2025
Model-free system identification of surface ships in waves via Hankel dynamic mode decomposition with control Giorgio Palma A. Serani Shawn Aram David W. Wundrow David Drazen Matteo Diez 70 0 0 17 Feb 2025
Koopman Learning with Episodic Memory William T. Redman Dean Huang M. Fonoberova Igor Mezić 97 0 0 08 Jan 2025
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions Jake Buzhardt C. Ricardo Constante-Amores Michael D. Graham 171 2 0 20 Nov 2024
Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction Manuel Brenner Christoph Jürgen Hemmer Zahra Monfared Daniel Durstewitz AI4CE 80 4 0 18 Oct 2024
On latent dynamics learning in nonlinear reduced order modeling N. Farenga S. Fresca Simone Brivio Andrea Manzoni AI4CE 69 1 0 27 Aug 2024
Learning Noise-Robust Stable Koopman Operator for Control with Hankel DMD Shahriar Akbar Sakib Shaowu Pan 112 0 0 13 Aug 2024
Enhanced Prediction of Multi-Agent Trajectories via Control Inference and State-Space Dynamics Yu Zhang Yongxiang Zou Haoyu Zhang Zeyu Liu Houcheng Li Long Cheng AI4CE 79 1 0 08 Aug 2024
Koopman Operators in Robot Learning Lu Shi Masih Haseli Giorgos Mamakoukas Daniel Bruder Ian Abraham Todd Murphey Jorge Cortes Konstantinos Karydis AI4CE 120 8 0 08 Aug 2024
Minimum Reduced-Order Models via Causal Inference Nan Chen Honghu Liu CML 53 0 0 29 Jun 2024
Recurrent Deep Kernel Learning of Dynamical Systems N. Botteghi Paolo Motta Andrea Manzoni P. Zunino Mengwu Guo 60 1 0 30 May 2024
Vector Field-Guided Learning Predictive Control for Motion Planning of Mobile Robots with Uncertain Dynamics Yang Lu Weijia Yao Yongqian Xiao Xinglong Zhang Xin Xu Yaonan Wang Dingbang Xiao 63 0 0 14 May 2024
Nonparametric Control Koopman Operators Petar Bevanda Bas Driessen Lucian-Cristian Iacob Roland Toth Stefan Sosnowski Sandra Hirche 105 2 0 12 May 2024
Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection Thorben Markmann Michiel Straat Barbara Hammer AI4CE 87 4 0 10 May 2024
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation Chuanqi Chen Nan Chen Jin-Long Wu AI4CE 78 4 0 10 Apr 2024
Systematic construction of continuous-time neural networks for linear dynamical systems Chinmay Datar Adwait Datar Felix Dietrich W. Schilders AI4TS 58 1 0 24 Mar 2024
Temporally Consistent Koopman Autoencoders for Forecasting Dynamical Systems I. Nayak Ananda Chakrabarty Mrinal Kumar Fernando L. Teixeira Debdipta Goswami 116 5 0 19 Mar 2024
Koopman Ensembles for Probabilistic Time Series Forecasting Anthony Frion Lucas Drumetz Guillaume Tochon M. Dalla Mura Albdeldjalil Aissa El Bey AI4TS 48 0 0 11 Mar 2024
Koopman-Assisted Reinforcement Learning Preston Rozwood Edward Mehrez Ludger Paehler Wen Sun Steven L. Brunton 109 10 0 04 Mar 2024
Out-of-Domain Generalization in Dynamical Systems Reconstruction Niclas Alexander Göring Florian Hess Manuel Brenner Zahra Monfared Daniel Durstewitz AI4CE 105 16 0 28 Feb 2024
Phase autoencoder for limit-cycle oscillators K. Yawata Kai Fukami Kunihiko Taira Hiroya Nakao 126 9 0 28 Feb 2024
Machine Learning based Prediction of Ditching Loads Henning Schwarz Micha Überrück J. Zemke Thomas Rung MU AI4CE 47 1 0 16 Feb 2024
RefreshNet: Learning Multiscale Dynamics through Hierarchical Refreshing Junaid Farooq Danish Rafiq Pantelis R. Vlachas M. A. Bazaz 59 0 0 24 Jan 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning Hao Liu Biraj Dahal Rongjie Lai Wenjing Liao AI4CE 60 5 0 19 Jan 2024
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder Priyam Gupta Peter J. Schmid D. Sipp T. Sayadi Georgios Rigas 118 5 0 16 Oct 2023
Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches Ricardo Constante-Amores Alec J. Linot Michael D. Graham 76 10 0 10 Oct 2023
Why should autoencoders work? Matthew D. Kvalheim E.D. Sontag 118 2 0 03 Oct 2023
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 118 0 0 27 Sep 2023
Interpretable learning of effective dynamics for multiscale systems Emmanuel Menier Sebastian Kaltenbach Mouadh Yagoubi Marc Schoenauer Petros Koumoutsakos AI4CE 79 7 0 11 Sep 2023
Neural Koopman prior for data assimilation Anthony Frion Lucas Drumetz M. Dalla Mura Guillaume Tochon Abdeldjalil Aissa El Bey AI4TS AI4CE 75 5 0 11 Sep 2023
Multi-fidelity reduced-order surrogate modeling Paolo Conti Mengwu Guo Andrea Manzoni A. Frangi Steven L. Brunton N. Kutz AI4CE 93 29 0 01 Sep 2023
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics P. Goyal Süleyman Yıldız P. Benner 89 3 0 26 Aug 2023
Learning to Predict 3D Rotational Dynamics from Images of a Rigid Body with Unknown Mass Distribution J. Mason Christine Allen-Blanchette Nicholas Zolman Elizabeth Davison Naomi Leonard 3DH 32 4 0 24 Aug 2023
Learning invariant representations of time-homogeneous stochastic dynamical systems Vladimir Kostic P. Novelli Riccardo Grazzi Karim Lounici Massimiliano Pontil 70 8 0 19 Jul 2023
Koopman operator learning using invertible neural networks Yuhuang Meng Jian-Kai Huang Yue Qiu 53 14 0 30 Jun 2023
PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator Shaowu Pan E. Kaiser Brian M. de Silva J. Nathan Kutz Steven L. Brunton 118 8 0 22 Jun 2023
Active-Learning-Driven Surrogate Modeling for Efficient Simulation of Parametric Nonlinear Systems Harshit Kapadia Lihong Feng P. Benner 36 11 0 09 Jun 2023
Generalized Teacher Forcing for Learning Chaotic Dynamics Florian Hess Zahra Monfared Manuela Brenner Daniel Durstewitz AI4CE 259 36 0 07 Jun 2023
Koopman Kernel Regression Petar Bevanda Maximilian Beier Armin Lederer Stefan Sosnowski Eyke Hüllermeier Sandra Hirche AI4TS 84 16 0 25 May 2023
Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing King Fai Yeh Paris D. L. Flood William T. Redman Pietro Lio 69 1 0 15 May 2023
On the lifting and reconstruction of nonlinear systems with multiple invariant sets Shaowu Pan Karthik Duraisamy 124 4 0 24 Apr 2023
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders Nimrod Berman Ilana D Naiman Omri Azencot CoGe 89 24 0 30 Mar 2023