Data-driven Model Reduction for Soft Robots via Lagrangian Operator Inference
Fuente:
arXiv
Saved in:
| Main Authors: | Sharma, Harsh, Adibnazari, Iman, Cervera-Torralba, Jacobo, Tolley, Michael T., Kramer, Boris |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Dynamic Shape Control of Soft Robots Enabled by Data-Driven Model Reduction
by: Adibnazari, Iman, et al.
Published: (2025)
by: Adibnazari, Iman, et al.
Published: (2025)
Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale dynamical systems
by: Sharma, Harsh, et al.
Published: (2022)
by: Sharma, Harsh, et al.
Published: (2022)
Structure-preserving Lift & Learn: Scientific machine learning for nonlinear conservative partial differential equations
by: Sharma, Harsh, et al.
Published: (2025)
by: Sharma, Harsh, et al.
Published: (2025)
Nonlinear energy-preserving model reduction with lifting transformations that quadratize the energy
by: Sharma, Harsh, et al.
Published: (2025)
by: Sharma, Harsh, et al.
Published: (2025)
Physically consistent predictive reduced-order modeling by enhancing Operator Inference with state constraints
by: Kim, Hyeonghun, et al.
Published: (2025)
by: Kim, Hyeonghun, et al.
Published: (2025)
Data-driven Model Reduction for Parameter-Dependent Matrix Equations via Operator Inference
by: Wen, Xuelian, et al.
Published: (2025)
by: Wen, Xuelian, et al.
Published: (2025)
Data-Driven Prediction of Dynamic Interactions Between Robot Appendage and Granular Material
by: Wang, Guanjin, et al.
Published: (2025)
by: Wang, Guanjin, et al.
Published: (2025)
Parametric Operator Inference to Simulate the Purging Process in Semiconductor Manufacturing
by: Kang, Seunghyon, et al.
Published: (2025)
by: Kang, Seunghyon, et al.
Published: (2025)
Data-Driven Reduced-Order Models for Port-Hamiltonian Systems with Operator Inference
by: Geng, Yuwei, et al.
Published: (2025)
by: Geng, Yuwei, et al.
Published: (2025)
Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems
by: Koike, Tomoki, et al.
Published: (2026)
by: Koike, Tomoki, et al.
Published: (2026)
Robo-GS: A Physics Consistent Spatial-Temporal Model for Robotic Arm with Hybrid Representation
by: Lou, Haozhe, et al.
Published: (2024)
by: Lou, Haozhe, et al.
Published: (2024)
Gradient Preserving Operator Inference: Data-Driven Reduced-Order Models for Equations with Gradient Structure
by: Geng, Yuwei, et al.
Published: (2024)
by: Geng, Yuwei, et al.
Published: (2024)
BC-ADMM: An Efficient Non-convex Constrained Optimizer with Robotic Applications
by: Pan, Zherong, et al.
Published: (2025)
by: Pan, Zherong, et al.
Published: (2025)
Adaptive Probabilistic ODE Solvers Without Adaptive Memory Requirements
by: Krämer, Nicholas
Published: (2024)
by: Krämer, Nicholas
Published: (2024)
A Generalized Matrix Inverse that is Consistent with Respect to Diagonal Transformations
by: Uhlmann, Jeffrey
Published: (2026)
by: Uhlmann, Jeffrey
Published: (2026)
Is there an optimal choice of configuration space for Lie group integration schemes applied to constrained MBS?
by: Mueller, Andreas, et al.
Published: (2024)
by: Mueller, Andreas, et al.
Published: (2024)
SNGR: Selective Non-Gaussian Refinement for Ambiguous SLAM Factor Graphs
by: Kulkarni, Anushka, et al.
Published: (2026)
by: Kulkarni, Anushka, et al.
Published: (2026)
The significance of the configuration space Lie group for the constraint satisfaction in numerical time integration of multibody systems
by: Mueller, Andreas, et al.
Published: (2024)
by: Mueller, Andreas, et al.
Published: (2024)
Data-driven Closure Strategies for Parametrized Reduced Order Models via Deep Operator Networks
by: Ivagnes, Anna, et al.
Published: (2025)
by: Ivagnes, Anna, et al.
Published: (2025)
Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference
by: Goyal, Pawan, et al.
Published: (2023)
by: Goyal, Pawan, et al.
Published: (2023)
Data-Driven Model Reduction using WeldNet: Windowed Encoders for Learning Dynamics
by: Dahal, Biraj, et al.
Published: (2025)
by: Dahal, Biraj, et al.
Published: (2025)
Data Complexity Estimates for Operator Learning
by: Kovachki, Nikola B., et al.
Published: (2024)
by: Kovachki, Nikola B., et al.
Published: (2024)
Global sensitivity analysis with limited data via sparsity-promoting D-MORPH regression: Application to char combustion
by: Lee, Dongjin, et al.
Published: (2023)
by: Lee, Dongjin, et al.
Published: (2023)
Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference
by: Gosea, Ion Victor, et al.
Published: (2024)
by: Gosea, Ion Victor, et al.
Published: (2024)
Nested Operator Inference for Adaptive Data-Driven Learning of Reduced-order Models
by: Aretz, Nicole, et al.
Published: (2025)
by: Aretz, Nicole, et al.
Published: (2025)
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
by: Tu, Renbo, et al.
Published: (2023)
by: Tu, Renbo, et al.
Published: (2023)
DeepRitzSplit Neural Operator for Phase-Field Models via Energy Splitting
by: Huang, Chih-Kang, et al.
Published: (2026)
by: Huang, Chih-Kang, et al.
Published: (2026)
Integral Operator Approaches for Scattered Data Fitting on Spheres
by: Lin, Shao-Bo
Published: (2024)
by: Lin, Shao-Bo
Published: (2024)
Latent Space Inference via Paired Autoencoders
by: Hart, Emma, et al.
Published: (2026)
by: Hart, Emma, et al.
Published: (2026)
Accuracy Evaluation of a Lightweight Analytic Vehicle Dynamics Model for Maneuver Planning
by: Ziehn, J. R., et al.
Published: (2024)
by: Ziehn, J. R., et al.
Published: (2024)
MgNO: Efficient Parameterization of Linear Operators via Multigrid
by: He, Juncai, et al.
Published: (2023)
by: He, Juncai, et al.
Published: (2023)
Sensor Model Identification via Simultaneous Model Selection and State Variable Determination
by: Brommer, Christian, et al.
Published: (2025)
by: Brommer, Christian, et al.
Published: (2025)
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
by: Zaspel, Peter, et al.
Published: (2024)
by: Zaspel, Peter, et al.
Published: (2024)
Domain Decomposition-based coupling of Operator Inference reduced order models via the Schwarz alternating method
by: Moore, Ian, et al.
Published: (2024)
by: Moore, Ian, et al.
Published: (2024)
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
by: Wang, Hong, et al.
Published: (2024)
by: Wang, Hong, et al.
Published: (2024)
Energy-Preserving Reduced Operator Inference for Efficient Design and Control
by: Koike, Tomoki, et al.
Published: (2024)
by: Koike, Tomoki, et al.
Published: (2024)
Matrix-Free Least Squares Solvers: Values, Gradients, and What to Do With Them
by: Roy, Hrittik, et al.
Published: (2025)
by: Roy, Hrittik, et al.
Published: (2025)
The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures
by: Adcock, Ben, et al.
Published: (2024)
by: Adcock, Ben, et al.
Published: (2024)
Learning the Hodgkin-Huxley Model with Operator Learning Techniques
by: Centofanti, Edoardo, et al.
Published: (2024)
by: Centofanti, Edoardo, et al.
Published: (2024)
Operator SVD with Neural Networks via Nested Low-Rank Approximation
by: Ryu, J. Jon, et al.
Published: (2024)
by: Ryu, J. Jon, et al.
Published: (2024)
Similar Items
-
Dynamic Shape Control of Soft Robots Enabled by Data-Driven Model Reduction
by: Adibnazari, Iman, et al.
Published: (2025) -
Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale dynamical systems
by: Sharma, Harsh, et al.
Published: (2022) -
Structure-preserving Lift & Learn: Scientific machine learning for nonlinear conservative partial differential equations
by: Sharma, Harsh, et al.
Published: (2025) -
Nonlinear energy-preserving model reduction with lifting transformations that quadratize the energy
by: Sharma, Harsh, et al.
Published: (2025) -
Physically consistent predictive reduced-order modeling by enhancing Operator Inference with state constraints
by: Kim, Hyeonghun, et al.
Published: (2025)