Learning Compositional Koopman Operators for Model-Based Control

18 October 2019

Yunzhu Li

Hao He

Jiajun Wu

Dina Katabi

Antonio Torralba

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Papers citing "Learning Compositional Koopman Operators for Model-Based Control"

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Title
Koopman Spectrum Nonlinear Regulators and Efficient Online Learning Motoya Ohnishi Isao Ishikawa Kendall Lowrey Masahiro Ikeda Sham Kakade Yoshinobu Kawahara 21 5 0 30 Jun 2021
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations Yingtao Luo Qiang Liu Yuntian Chen Wenbo Hu Tian Tian Jun Zhu DiffM 53 4 0 02 Jun 2021
Deformable Linear Object Prediction Using Locally Linear Latent Dynamics Wenbo Zhang Karl Schmeckpeper Pratik Chaudhari Kostas Daniilidis AI4CE 29 23 0 26 Mar 2021
Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects Zehang Weng Fabian Paus Anastasiia Varava Hang Yin Tamim Asfour Danica Kragic AI4CE 16 18 0 04 Mar 2021
A Differential Geometry Perspective on Orthogonal Recurrent Models Omri Azencot N. Benjamin Erichson M. Ben-Chen Michael W. Mahoney AI4CE 13 5 0 18 Feb 2021
An Operator Theoretic Approach for Analyzing Sequence Neural Networks Ilana D Naiman Omri Azencot 27 10 0 15 Feb 2021
Neuro-algorithmic Policies enable Fast Combinatorial Generalization Marin Vlastelica Michal Rolínek Georg Martius 35 17 0 15 Feb 2021
Noisy Recurrent Neural Networks S. H. Lim N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 14 52 0 09 Feb 2021
Meta-Learning for Koopman Spectral Analysis with Short Time-series Tomoharu Iwata Yoshinobu Kawahara AI4TS 36 0 0 09 Feb 2021
Faster Policy Learning with Continuous-Time Gradients Samuel K. Ainsworth Kendall Lowrey John Thickstun Zaïd Harchaoui S. Srinivasa 19 11 0 12 Dec 2020
Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics Tomoharu Iwata Yoshinobu Kawahara 16 12 0 11 Dec 2020
IV-Posterior: Inverse Value Estimation for Interpretable Policy Certificates Tatiana Lopez-Guevara Michael G. Burke Nick K. Taylor Kartic Subr OffRL 30 0 0 30 Nov 2020
DeepKoCo: Efficient latent planning with a task-relevant Koopman representation B. V. D. Heijden L. Ferranti Jens Kober Robert Babuška 16 6 0 25 Nov 2020
Transformers for Modeling Physical Systems N. Geneva N. Zabaras AI4CE 16 139 0 04 Oct 2020
Causal Discovery in Physical Systems from Videos Yunzhu Li Antonio Torralba Anima Anandkumar Dieter Fox Animesh Garg CML 28 103 0 01 Jul 2020
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers Kiwon Um R. Brand Yun Fei Fei Philipp Holl N. Thürey AI4CE 21 257 0 30 Jun 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 41 25 0 23 Jun 2020
NewtonianVAE: Proportional Control and Goal Identification from Pixels via Physical Latent Spaces Miguel Jaques Michael G. Burke Timothy M. Hospedales DRL 12 20 0 02 Jun 2020
A First Principles Approach for Data-Efficient System Identification of Spring-Rod Systems via Differentiable Physics Engines Kun Wang Mridul Aanjaneya Kostas Bekris PINN 10 21 0 28 Apr 2020
Visual Grounding of Learned Physical Models Yunzhu Li Toru Lin Kexin Yi Daniel M. Bear Daniel L. K. Yamins Jiajun Wu J. Tenenbaum Antonio Torralba OOD OCL AI4CE PINN 37 79 0 28 Apr 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 24 143 0 04 Mar 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 109 49 0 27 Feb 2020
Learning Group Structure and Disentangled Representations of Dynamical Environments Robin Quessard Thomas D. Barrett W. Clements DRL 14 20 0 17 Feb 2020
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang T. Ullman Antonio Torralba J. Tenenbaum AI4CE OCL 241 439 0 01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 283 1,401 0 01 Dec 2016