Cover Image

KoopGen: Koopman Generator Networks for Representing and Predicting Dynamical Systems with Continuous Spectra

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Su, Liangyu, Shu, Jun, Liu, Rui, Meng, Deyu, Xu, Zongben
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Memory Efficiency for Training KANs via Meta Learning
by: Zhao, Zhangchi, et al.
Published: (2025)

A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws
by: Shu, Jun, et al.
Published: (2026)

ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
by: Xu, Yuanchao, et al.
Published: (2025)

Feed Two Birds with One Scone: Exploiting Function-Space Regularization for Both OOD Robustness and ID Fine-Tuning Performance
by: Yuan, Xiang, et al.
Published: (2025)

KoopCast: Trajectory Forecasting via Koopman Operators
by: Lee, Jungjin, et al.
Published: (2025)

DeepKoopFormer: A Koopman Enhanced Transformer Based Architecture for Time Series Forecasting
by: Forootani, Ali, et al.
Published: (2025)

Rotation Equivariant Proximal Operator for Deep Unfolding Methods in Image Restoration
by: Fu, Jiahong, et al.
Published: (2023)

KoopAGRU: A Koopman-based Anomaly Detection in Time-Series using Gated Recurrent Units
by: Yahia, Issam Ait, et al.
Published: (2025)

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning
by: Li, Alice Kate, et al.
Published: (2025)

Understanding the Generalization of Bilevel Programming in Hyperparameter Optimization: A Tale of Bias-Variance Decomposition
by: Zhou, Yubo, et al.
Published: (2026)

RoboKoop: Efficient Control Conditioned Representations from Visual Input in Robotics using Koopman Operator
by: Kumawat, Hemant, et al.
Published: (2024)

Quantum-Inspired Analysis of Neural Network Vulnerabilities: The Role of Conjugate Variables in System Attacks
by: Zhang, Jun-Jie, et al.
Published: (2024)

Representing Neural Network Layers as Linear Operations via Koopman Operator Theory
by: Aswani, Nishant Suresh, et al.
Published: (2024)

Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems
by: Zhou, Ruikun, et al.
Published: (2024)

Temporally Consistent Koopman Autoencoders for Forecasting Dynamical Systems
by: Nayak, Indranil, et al.
Published: (2024)

Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting
by: Grozavescu, Rares, et al.
Published: (2026)

Transformer with Koopman-Enhanced Graph Convolutional Network for Spatiotemporal Dynamics Forecasting
by: Wang, Zekai, et al.
Published: (2025)

OmniXAS: A Universal Deep-Learning Framework for Materials X-ray Absorption Spectra
by: Kharel, Shubha R., et al.
Published: (2024)

Data-Distill-Net: A Data Distillation Approach Tailored for Reply-based Continual Learning
by: Liao, Wenyang, et al.
Published: (2025)

Koopman-based Prediction of Connectivity for Flying Ad Hoc Networks
by: Krishnan, Sivaram, et al.
Published: (2025)

NeuroKoopman Dynamic Causal Discovery
by: Adesunkanmi, Rahmat, et al.
Published: (2024)

GenUQ: Predictive Uncertainty Estimates via Generative Hyper-Networks
by: Yen, Tian Yu, et al.
Published: (2025)

Generalizing across Temporal Domains with Koopman Operators
by: Zeng, Qiuhao, et al.
Published: (2024)

A Self-Adaptive Frequency Domain Network for Continuous Intraoperative Hypotension Prediction
by: Zeng, Xian, et al.
Published: (2025)

Condition Numbers and Eigenvalue Spectra of Shallow Networks on Spheres
by: Liu, Xinliang, et al.
Published: (2025)

Unveiling the Mechanism of Continuous Representation Full-Waveform Inversion: A Wave Based Neural Tangent Kernel Framework
by: Chen, Ruihua, et al.
Published: (2026)

Koopman Autoencoders Learn Neural Representation Dynamics
by: Aswani, Nishant Suresh, et al.
Published: (2025)

Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network
by: Chen, Chuanqi, et al.
Published: (2025)

Koopman operator-based discussion on partial observation in stochastic systems
by: Ohkubo, Jun
Published: (2025)

Residual Koopman Spectral Profiling for Predicting and Preventing Transformer Training Instability
by: Kim, Bum Jun, et al.
Published: (2026)

Learning-based Multi-continuum Model for Multiscale Flow Problems
by: Wang, Fan, et al.
Published: (2024)

NetFlowGen: Leveraging Generative Pre-training for Network Traffic Dynamics
by: Zhou, Jiawei, et al.
Published: (2024)

A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
by: Ji, Shengjiao, et al.
Published: (2025)

Extraction of nonlinearity in neural networks with Koopman operator
by: Sugishita, Naoki, et al.
Published: (2024)

From SGD to Spectra: A Theory of Neural Network Weight Dynamics
by: Olsen, Brian Richard, et al.
Published: (2025)

GenEFT: Understanding Statics and Dynamics of Model Generalization via Effective Theory
by: Baek, David D., et al.
Published: (2024)

Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration
by: Tan, Feiyu, et al.
Published: (2026)

Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches
by: Constante-Amores, C. Ricardo, et al.
Published: (2023)

On the Generalisation of Koopman Representations for Chaotic System Control
by: Hjikakou, Kyriakos, et al.
Published: (2025)

Dual-CBA: Improving Online Continual Learning via Dual Continual Bias Adaptors from a Bi-level Optimization Perspective
by: Wang, Quanziang, et al.
Published: (2024)