Imagen de Portada

Time-adaptive HénonNets for separable Hamiltonian systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Janik, Konrad, Benner, Peter
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Time-adaptive SympNets for separable Hamiltonian systems
por: Janik, Konrad, et al.
Publicado: (2025)

Symplectic convolutional neural networks
por: Yıldız, Süleyman, et al.
Publicado: (2025)

Data-Driven Identification of Quadratic Representations for Nonlinear Hamiltonian Systems using Weakly Symplectic Liftings
por: Yildiz, Süleyman, et al.
Publicado: (2023)

Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs
por: Sun, Shuwen, et al.
Publicado: (2025)

Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning
por: Goyal, Pawan, et al.
Publicado: (2022)

Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning
por: Goyal, Pawan, et al.
Publicado: (2021)

Comparative Analysis of Predicting Subsequent Steps in Hénon Map
por: S, Vismaya V, et al.
Publicado: (2024)

Data-Augmented Predictive Deep Neural Network: Enhancing the extrapolation capabilities of non-intrusive surrogate models
por: Sun, Shuwen, et al.
Publicado: (2024)

Structure-preserving learning for multi-symplectic PDEs
por: Yıldız, Süleyman, et al.
Publicado: (2024)

Stability-Certified Learning of Control Systems with Quadratic Nonlinearities
por: Duff, Igor Pontes, et al.
Publicado: (2024)

Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference
por: Goyal, Pawan, et al.
Publicado: (2023)

GFlowNets for Hamiltonian decomposition in groups of compatible operators
por: Huidobro-Meezs, Isaac L., et al.
Publicado: (2024)

SynCoTrain: A Dual Classifier PU-learning Framework for Synthesizability Prediction
por: Amariamir, Sasan, et al.
Publicado: (2024)

GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
por: Forootani, Ali, et al.
Publicado: (2024)

Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets
por: Jacot, Arthur, et al.
Publicado: (2024)

Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
por: Zhong, Yaofeng Desmond, et al.
Publicado: (2019)

Hamiltonian Score Matching and Generative Flows
por: Holderrieth, Peter, et al.
Publicado: (2024)

GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
por: Bou-Rabee, Nawaf, et al.
Publicado: (2024)

Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
por: Zaspel, Peter, et al.
Publicado: (2024)

Deep Neural Nets as Hamiltonians
por: Winer, Mike, et al.
Publicado: (2025)

Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring
por: Marín, Javier
Publicado: (2024)

Subspace-Distance-Enabled Active Learning for Efficient Data-Driven Model Reduction of Parametric Dynamical Systems
por: Kapadia, Harshit, et al.
Publicado: (2025)

DCSI -- An improved measure of cluster separability based on separation and connectedness
por: Gauss, Jana, et al.
Publicado: (2023)

When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
por: Treven, Lenart, et al.
Publicado: (2024)

Aspects of human memory and Large Language Models
por: Janik, Romuald A.
Publicado: (2023)

Solve sparse PCA problem by employing Hamiltonian system and leapfrog method
por: Tran, Loc Hoang
Publicado: (2025)

Learning partially observed systems with neural Hamiltonian ordinary differential equations
por: Meltzer, Sunniva, et al.
Publicado: (2026)

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models
por: Hagemann, Paul, et al.
Publicado: (2025)

A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas
por: Benzin, Janik-Vasily, et al.
Publicado: (2023)

Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference
por: Gosea, Ion Victor, et al.
Publicado: (2024)

BiTimeCrossNet: Time-Aware Self-Supervised Learning for Pediatric Sleep
por: Pandey, Saurav Raj, et al.
Publicado: (2026)

Unsupervised domain adaptation for radioisotope identification in gamma spectroscopy
por: Lalor, Peter, et al.
Publicado: (2026)

Predicting adaptively chosen observables in quantum systems
por: Huang, Jerry, et al.
Publicado: (2024)

Hamiltonian Graph Inference Networks: Joint structure discovery and dynamics prediction for lattice Hamiltonian systems from trajectory data
por: Geng, Ru, et al.
Publicado: (2026)

Hamiltonian-based neural networks for systems under nonholonomic constraints
por: T., Ignacio Puiggros, et al.
Publicado: (2024)

Diffeomorphic Temporal Alignment Nets for Time-series Joint Alignment and Averaging
por: Weber, Ron Shapira, et al.
Publicado: (2025)

AdaWaveNet: Adaptive Wavelet Network for Time Series Analysis
por: Yu, Han, et al.
Publicado: (2024)

In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks
por: Xu, Shangqing, et al.
Publicado: (2026)

ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis
por: Cheng, Mingyue, et al.
Publicado: (2024)

Scalable h-adaptive probabilistic solver for time-independent and time-dependent systems
por: Thakur, Akshay, et al.
Publicado: (2025)