Data-Driven Identification of Quadratic Representations for Nonlinear Hamiltonian Systems using Weakly Symplectic Liftings
Fuente:
arXiv
Saved in:
| Main Authors: | Yildiz, Süleyman, Goyal, Pawan, Bendokat, Thomas, Benner, Peter |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning
by: Goyal, Pawan, et al.
Published: (2022)
by: Goyal, Pawan, et al.
Published: (2022)
Structure-preserving learning for multi-symplectic PDEs
by: Yıldız, Süleyman, et al.
Published: (2024)
by: Yıldız, Süleyman, et al.
Published: (2024)
Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning
by: Goyal, Pawan, et al.
Published: (2021)
by: Goyal, Pawan, et al.
Published: (2021)
Symplectic convolutional neural networks
by: Yıldız, Süleyman, et al.
Published: (2025)
by: Yıldız, Süleyman, et al.
Published: (2025)
Stability-Certified Learning of Control Systems with Quadratic Nonlinearities
by: Duff, Igor Pontes, et al.
Published: (2024)
by: Duff, Igor Pontes, et al.
Published: (2024)
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)
GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
by: Forootani, Ali, et al.
Published: (2024)
by: Forootani, Ali, et al.
Published: (2024)
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)
Time-adaptive HénonNets for separable Hamiltonian systems
by: Janik, Konrad, et al.
Published: (2025)
by: Janik, Konrad, et al.
Published: (2025)
Time-adaptive SympNets for separable Hamiltonian systems
by: Janik, Konrad, et al.
Published: (2025)
by: Janik, Konrad, et al.
Published: (2025)
Symplectic Inductive Bias for Data-Driven Target Reachability in Hamiltonian Systems
by: Ouyang, Zhuo, et al.
Published: (2026)
by: Ouyang, Zhuo, et al.
Published: (2026)
Modelling Gas Networks with Compressors: A port-Hamiltonian Approach
by: Bendokat, Thomas, et al.
Published: (2024)
by: Bendokat, Thomas, et al.
Published: (2024)
Modelling Gas Networks with Compressors: A port‐Hamiltonian Approach
by: Thomas Bendokat, et al.
Published: (2024)
by: Thomas Bendokat, et al.
Published: (2024)
Koopman Identification of Nonlinear Systems via Reservoir Liftings
by: Gu, Weibin, et al.
Published: (2026)
by: Gu, Weibin, et al.
Published: (2026)
Balanced Truncation of Descriptor Systems with a Quadratic Output
by: Przybilla, Jennifer, et al.
Published: (2024)
by: Przybilla, Jennifer, et al.
Published: (2024)
Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks
by: Wu, Zongyu, et al.
Published: (2025)
by: Wu, Zongyu, et al.
Published: (2025)
Learning Generalized Hamiltonians using fully Symplectic Mappings
by: Choudhary, Harsh, et al.
Published: (2024)
by: Choudhary, Harsh, et al.
Published: (2024)
Active Sampling of Interpolation Points to Identify Dominant Subspaces for Model Reduction
by: Reddig, Celine, et al.
Published: (2024)
by: Reddig, Celine, et al.
Published: (2024)
A physics-encoded Fourier neural operator approach for surrogate modeling of divergence-free stress fields in solids
by: Khorrami, Mohammad S., et al.
Published: (2024)
by: Khorrami, Mohammad S., et al.
Published: (2024)
Subspace-Distance-Enabled Active Learning for Efficient Data-Driven Model Reduction of Parametric Dynamical Systems
by: Kapadia, Harshit, et al.
Published: (2025)
by: Kapadia, Harshit, et al.
Published: (2025)
Symplectic Structure-Aware Hamiltonian (Graph) Embeddings
by: Liu, Jiaxu, et al.
Published: (2023)
by: Liu, Jiaxu, et al.
Published: (2023)
Hamiltonian Matching for Symplectic Neural Integrators
by: Canizares, Priscilla, et al.
Published: (2024)
by: Canizares, Priscilla, et al.
Published: (2024)
Symplectic Reservoir Representation of Legendre Dynamics
by: Fong, Robert Simon, et al.
Published: (2025)
by: Fong, Robert Simon, et al.
Published: (2025)
LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification
by: Singh, Arunabh, et al.
Published: (2024)
by: Singh, Arunabh, et al.
Published: (2024)
Beyond Isotropy in JEPAs: Hamiltonian Geometry and Symplectic Prediction
by: Alvarez, Robert Jenkinson
Published: (2026)
by: Alvarez, Robert Jenkinson
Published: (2026)
A CFL-type Condition and Theoretical Insights for Discrete-Time Sparse Full-Order Model Inference
by: Gkimisis, Leonidas, et al.
Published: (2025)
by: Gkimisis, Leonidas, et al.
Published: (2025)
Data-Augmented Predictive Deep Neural Network: Enhancing the extrapolation capabilities of non-intrusive surrogate models
by: Sun, Shuwen, et al.
Published: (2024)
by: Sun, Shuwen, et al.
Published: (2024)
Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs
by: Sun, Shuwen, et al.
Published: (2025)
by: Sun, Shuwen, et al.
Published: (2025)
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
by: Zhong, Yaofeng Desmond, et al.
Published: (2019)
by: Zhong, Yaofeng Desmond, et al.
Published: (2019)
On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations
by: Rajkumar, Santosh Mohan, et al.
Published: (2026)
by: Rajkumar, Santosh Mohan, et al.
Published: (2026)
Data-Driven Observability Analysis for Nonlinear Stochastic Systems
by: Massiani, Pierre-François, et al.
Published: (2023)
by: Massiani, Pierre-François, et al.
Published: (2023)
Bridging Philosophy and Machine Learning: A Structuralist Framework for Classifying Neural Network Representations
by: Culcu, Yildiz
Published: (2025)
by: Culcu, Yildiz
Published: (2025)
Federated Nonlinear System Identification
by: Tupe, Omkar, et al.
Published: (2025)
by: Tupe, Omkar, et al.
Published: (2025)
AC-SINDy: Compositional Sparse Identification of Nonlinear Dynamics
by: Racioppo, Peter
Published: (2026)
by: Racioppo, Peter
Published: (2026)
Lifting Biomolecular Data Acquisition
by: Weinstein, Eli N., et al.
Published: (2025)
by: Weinstein, Eli N., et al.
Published: (2025)
Generalization Guarantees on Data-Driven Tuning of Gradient Descent with Langevin Updates
by: Goyal, Saumya, et al.
Published: (2026)
by: Goyal, Saumya, et al.
Published: (2026)
Latent Diffusion Pretraining for Crystal Property Prediction
by: Mukherjee, Shrimon, et al.
Published: (2026)
by: Mukherjee, Shrimon, et al.
Published: (2026)
Data-Driven Computing Methods for Nonlinear Physics Systems with Geometric Constraints
by: Tong, Yunjin
Published: (2024)
by: Tong, Yunjin
Published: (2024)
Optimal Control of Probabilistic Dynamics Models via Mean Hamiltonian Minimization
by: Leeftink, David, et al.
Published: (2025)
by: Leeftink, David, et al.
Published: (2025)
Periodic Materials Generation using Text-Guided Joint Diffusion Model
by: Das, Kishalay, et al.
Published: (2025)
by: Das, Kishalay, et al.
Published: (2025)
Similar Items
-
Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning
by: Goyal, Pawan, et al.
Published: (2022) -
Structure-preserving learning for multi-symplectic PDEs
by: Yıldız, Süleyman, et al.
Published: (2024) -
Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning
by: Goyal, Pawan, et al.
Published: (2021) -
Symplectic convolutional neural networks
by: Yıldız, Süleyman, et al.
Published: (2025) -
Stability-Certified Learning of Control Systems with Quadratic Nonlinearities
by: Duff, Igor Pontes, et al.
Published: (2024)