Cover Image

Unveiling the Actual Performance of Neural-based Models for Equation Discovery on Graph Dynamical Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cappi, Riccardo, Frazzetto, Paolo, Navarin, Nicolò, Sperduti, Alessandro
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Iterative In-Context Learning to Enhance LLMs Abstract Reasoning: The Case-Study of Algebraic Tasks
by: Fioravanti, Stefano, et al.
Published: (2025)

A tree-based kernel for graphs with continuous attributes
by: Martino, Giovanni Da San, et al.
Published: (2015)

Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
by: Muschalik, Maximilian, et al.
Published: (2025)

From Text to Talent: A Pipeline for Extracting Insights from Candidate Profiles
by: Frazzetto, Paolo, et al.
Published: (2025)

A City-Scale Dataset of Traffic Flows, Travel Times, and Urban Context
by: Cappi, Riccardo, et al.
Published: (2026)

A Spectral Interpretation of Redundancy in a Graph Reservoir
by: Bison, Anna, et al.
Published: (2025)

Online Continual Graph Learning
by: Donghi, Giovanni, et al.
Published: (2025)

IFH: a Diffusion Framework for Flexible Design of Graph Generative Models
by: Cognolato, Samuel, et al.
Published: (2024)

The Unreasonable Effectiveness of Randomized Representations in Online Continual Graph Learning
by: Donghi, Giovanni, et al.
Published: (2025)

Analysis of Dirichlet Energies as Over-smoothing Measures
by: Bison, Anna, et al.
Published: (2025)

Learning neuro-symbolic convergent term rewriting systems
by: Petruzzellis, Flavio, et al.
Published: (2025)

Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models
by: Petruzzellis, Flavio, et al.
Published: (2024)

Recurrent Deep Kernel Learning of Dynamical Systems
by: Botteghi, Nicolò, et al.
Published: (2024)

IGDA: Interactive Graph Discovery through Large Language Model Agents
by: Havrilla, Alex, et al.
Published: (2025)

Interpretable Neural System Dynamics: Combining Deep Learning with System Dynamics Modeling to Support Critical Applications
by: D'Elia, Riccardo
Published: (2025)

Cooperative Online Learning with Feedback Graphs
by: Cesa-Bianchi, Nicolò, et al.
Published: (2021)

Automating the Discovery of Partial Differential Equations in Dynamical Systems
by: Li, Weizhen, et al.
Published: (2024)

Automated Discovery of Functional Actual Causes in Complex Environments
by: Chuck, Caleb, et al.
Published: (2024)

Graph Neural Network and Transformer Integration for Unsupervised System Anomaly Discovery
by: Zi, Yun, et al.
Published: (2025)

Latent Field Discovery In Interacting Dynamical Systems With Neural Fields
by: Kofinas, Miltiadis, et al.
Published: (2023)

Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics
by: Chen, Yenho, et al.
Published: (2024)

Graphs Unveiled: Graph Neural Networks and Graph Generation
by: Kovács, László, et al.
Published: (2024)

Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning
by: Berndt, Torben, et al.
Published: (2025)

Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems
by: Kramer, Stefan, et al.
Published: (2023)

Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations
by: Qin, Tiexin, et al.
Published: (2023)

Non-Parametric Learning of Stochastic Differential Equations with Non-asymptotic Fast Rates of Convergence
by: Bonalli, Riccardo, et al.
Published: (2023)

Deep Invertible Autoencoders for Dimensionality Reduction of Dynamical Systems
by: Botteghi, Nicolò, et al.
Published: (2026)

Amortized Equation Discovery in Hybrid Dynamical Systems
by: Liu, Yongtuo, et al.
Published: (2024)

Dynamic Regret Reduces to Kernelized Static Regret
by: Jacobsen, Andrew, et al.
Published: (2025)

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
by: Bergna, Richard, et al.
Published: (2024)

GKNet: Graph Kalman Filtering and Model Inference via Model-based Deep Learning
by: Sabbaqi, Mohammad, et al.
Published: (2025)

Unveiling Mode Connectivity in Graph Neural Networks
by: Li, Bingheng, et al.
Published: (2025)

Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond
by: Shi, Dai, et al.
Published: (2025)

Controlled Langevin Dynamics for Sampling of Feedforward Neural Networks Trained with Minibatches
by: Zambon, Alessandro, et al.
Published: (2026)

Safely Learning Controlled Stochastic Dynamics
by: Brogat-Motte, Luc, et al.
Published: (2025)

Conformal Load Prediction with Transductive Graph Autoencoders
by: Luo, Rui, et al.
Published: (2024)

Graph Network-based Structural Simulator: Graph Neural Networks for Structural Dynamics
by: Lucchetti, Alessandro, et al.
Published: (2025)

Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
by: Mercatali, Giangiacomo, et al.
Published: (2024)

Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems
by: Bishnoi, Suresh, et al.
Published: (2022)

On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
by: Gravina, Alessio, et al.
Published: (2024)