Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems

Research article (Physica D Nonlinear Phenomena, 2021) · cited 63× · AI/ML
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Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems

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Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems. Retrieved May 24, 2026, from https://4ort.xyz/entity/hamiltonian-operator-inference-physics-preserving-learning-of-reduced-order-models-for-canonical-hamiltonian-systems
MLA “Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hamiltonian-operator-inference-physics-preserving-learning-of-reduced-order-models-for-canonical-hamiltonian-systems.
BibTeX @misc{4ortxyz_hamiltonian-operator-inference-physics-preserving-learning-of-reduced-order-models-for-canonical-hamiltonian-systems_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hamiltonian operator inference: Physics-preserving learning of reduced-order models for canonical Hamiltonian systems}}, year = {2026}, url = {https://4ort.xyz/entity/hamiltonian-operator-inference-physics-preserving-learning-of-reduced-order-models-for-canonical-hamiltonian-systems}, note = {Accessed: 2026-05-24}}
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