Image de couverture de livre

Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Khosrovian, Razmik Arman, Yaguchi, Takaharu, Yoshimura, Hiroaki, Matsubara, Takashi
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Number Theoretic Accelerated Learning of Physics-Informed Neural Networks
par: Matsubara, Takashi, et autres
Publié: (2023)

Learning Hamiltonian Density Using DeepONet
par: Xu, Baige, et autres
Publié: (2025)

Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
par: Furuya, Takashi, et autres
Publié: (2026)

Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs
par: Tanaka, Yusuke, et autres
Publié: (2024)

Symplectic Neural Operators for Learning Infinite Dimensional Hamiltonian Systems
par: Makara, Yeang, et autres
Publié: (2026)

CLPNets: Coupled Lie-Poisson Neural Networks for Multi-Part Hamiltonian Systems with Symmetries
par: Eldred, Christopher, et autres
Publié: (2024)

Object-Centric World Models for Causality-Aware Reinforcement Learning
par: Nishimoto, Yosuke, et autres
Publié: (2025)

Graph Neural Network Causal Explanation via Neural Causal Models
par: Behnam, Arman, et autres
Publié: (2024)

Modeling Latent Non-Linear Dynamical System over Time Series
par: Fujiwara, Ren, et autres
Publié: (2024)

PINNs Failure Modes are Overfitting
par: Andersen, Nigel T., et autres
Publié: (2026)

Online Adaptive Reinforcement Learning with Echo State Networks for Non-Stationary Dynamics
par: Yoshimura, Aoi, et autres
Publié: (2026)

Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach
par: Eliasof, Moshe, et autres
Publié: (2023)

Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series
par: Fujiwara, Ren, et autres
Publié: (2026)

Interpretable Dynamic Network Modeling of Tensor Time Series via Kronecker Time-Varying Graphical Lasso
par: Higashiguchi, Shingo, et autres
Publié: (2026)

Multi-agent Reinforcement Learning for Dynamic Dispatching in Material Handling Systems
par: Lee, Xian Yeow, et autres
Publié: (2024)

PHyCLIP: $\ell_1$-Product of Hyperbolic Factors Unifies Hierarchy and Compositionality in Vision-Language Representation Learning
par: Yoshikawa, Daiki, et autres
Publié: (2025)

P-DROP: Poisson-Based Dropout for Graph Neural Networks
par: Yun, Hyunsik
Publié: (2025)

Multi-Agent Decision Transformers for Dynamic Dispatching in Material Handling Systems Leveraging Enterprise Big Data
par: Lee, Xian Yeow, et autres
Publié: (2024)

Privacy-Preserving Verifiable Neural Network Inference Service
par: Riasi, Arman, et autres
Publié: (2024)

Domain-decoupled Physics-informed Neural Networks with Closed-form Gradients for Fast Model Learning of Dynamical Systems
par: Krauss, Henrik, et autres
Publié: (2024)

Enriched Physics-informed Neural Networks for Dynamic Poisson-Nernst-Planck Systems
par: Huang, Xujia, et autres
Publié: (2024)

From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach
par: Nguyen, Tuan, et autres
Publié: (2023)

A Transition System Abstraction Framework for Neural Network Dynamical System Models
par: Yang, Yejiang, et autres
Publié: (2024)

A Novel Neural Filter to Improve Accuracy of Neural Network Models of Dynamic Systems
par: Oveissi, Parham, et autres
Publié: (2024)

Improving Spatial Allocation for Energy System Coupling with Graph Neural Networks
par: Mu, Xuanhao, et autres
Publié: (2026)

A Model of Causal Explanation on Neural Networks for Tabular Data
par: Isozaki, Takashi, et autres
Publié: (2025)

Dynamic Multi-Network Mining of Tensor Time Series
par: Obata, Kohei, et autres
Publié: (2024)

On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
par: Gravina, Alessio, et autres
Publié: (2024)

Bayesian Neural Networks with Domain Knowledge Priors
par: Sam, Dylan, et autres
Publié: (2024)

Batch Normalization for Neural Networks on Complex Domains
par: Nguyen, Xuan Son, et autres
Publié: (2026)

Generative System Dynamics in Recurrent Neural Networks
par: Casoni, Michele, et autres
Publié: (2025)

Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks
par: Michałowska, Katarzyna, et autres
Publié: (2023)

ATM-Net: Adaptive Termination and Multi-Precision Neural Networks for Energy-Harvested Edge Intelligence
par: Solanki, Neeraj, et autres
Publié: (2025)

FredNormer: Frequency Domain Normalization for Non-stationary Time Series Forecasting
par: Piao, Xihao, et autres
Publié: (2024)

Discrete Dirac structures and discrete Lagrange--Dirac dynamical systems in mechanics
par: Peng, Linyu, et autres
Publié: (2024)

Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions
par: Nauck, Christian, et autres
Publié: (2024)

EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
par: Kotoge, Rikuto, et autres
Publié: (2025)

Physics-informed Neural Networks for Encoding Dynamics in Real Physical Systems
par: Alsharif, Hamza
Publié: (2024)

Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study
par: Kang, Qiyu, et autres
Publié: (2024)

Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning
par: Matsubara, Takuo
Publié: (2024)