Cover Image

A Generative Adversarial Graph Neural Network for Synthetic Time Series Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gregnanin, Marco, De Smedt, Johannes, Gnecco, Giorgio, Parton, Maurizio
Format:	Preprint
Published:	2026
Subjects:	Computational Engineering, Finance, and Science Computational Finance
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Statistical Significance of the Inclusion of Graph Neural Networks in the Financial Time Series Forecasting Problem
by: Gregnanin, Marco, et al.
Published: (2026)

Dynamic Hypergraph Representation Learning for Multivariate Time Series without Prior Knowledge
by: Gregnanin, Marco, et al.
Published: (2026)

Pre-training Time Series Models with Stock Data Customization
by: Wang, Mengyu, et al.
Published: (2025)

Using Graph Neural Networks and Frequency Domain Data for Automated Operational Modal Analysis of Populations of Structures
by: Jian, Xudong, et al.
Published: (2024)

Categorising SME Bank Transactions with Machine Learning and Synthetic Data Generation
by: Alessandro, Aluffi Pietro, et al.
Published: (2025)

Data Compression for Time Series Modelling: A Case Study of Smart Grid Demand Forecasting
by: Lykkegaard, Mikkel Bue, et al.
Published: (2025)

Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting
by: Yang, Jiarui, et al.
Published: (2024)

KANOP: A Data-Efficient Option Pricing Model using Kolmogorov-Arnold Networks
by: Handal, Rushikesh, et al.
Published: (2024)

Synthetic Data for Discriminating Serotonergic Neurons using Convolutional Neural Networks
by: Corradetti, Daniele, et al.
Published: (2024)

Prob-cGAN: A Probabilistic Conditional Generative Adversarial Network for LSD1 Inhibitor Activity Prediction
by: Wang, Hanyang
Published: (2024)

AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets
by: Fan, Tianyu, et al.
Published: (2025)

GO-GAN: Geometry Optimization Generative Adversarial Network for Achieving Optimized Structures with Targeted Physical Properties
by: Padmaprabhan, A., et al.
Published: (2025)

Graph Neural Network-Based Topology Optimization for Self-Supporting Structures in Additive Manufacturing
by: Tabarraei, Alireza, et al.
Published: (2025)

Generating Synthetic Genotypes using Diffusion Models
by: Kenneweg, Philip, et al.
Published: (2024)

Off-the-Shelf Neural Network Architectures for Forex Time Series Prediction come at a Cost
by: Zafeiriou, Theodoros, et al.
Published: (2024)

FinMultiTime: A Four-Modal Bilingual Dataset for Financial Time-Series Analysis
by: Xu, Wenyan, et al.
Published: (2025)

Synthetic Time Series Data Generation for Healthcare Applications: A PCG Case Study
by: Jamshidi, Ainaz, et al.
Published: (2024)

Graph Neural Network Approach to Predict the Effects of Road Capacity Reduction Policies: A Case Study for Paris, France
by: Natterer, Elena, et al.
Published: (2024)

Physics-informed, Generative Adversarial Design of Funicular Shells
by: Lourenço, Rúben, et al.
Published: (2026)

GRAPPA -- A Hybrid Graph Neural Network for Predicting Pure Component Vapor Pressures
by: Hoffmann, Marco, et al.
Published: (2025)

Networked Markets, Fragmented Data: Adaptive Graph Learning for Customer Risk Analytics and Policy Design
by: Zheng, Lecheng, et al.
Published: (2025)

Transfer Learning in Financial Time Series with Gramian Angular Field
by: Long, Hou-Wan, et al.
Published: (2025)

Physics Informed Neural Networks for Modeling of 3D Flow-Thermal Problems with Sparse Domain Data
by: Bhatnagar, Saakaar, et al.
Published: (2023)

Error Approximation and Bias Correction in Dynamic Problems using a Recurrent Neural Network/Finite Element Hybrid Model
by: von Tresckow, Moritz, et al.
Published: (2023)

Constitutive Manifold Neural Networks
by: Schuttert, Wouter J., et al.
Published: (2025)

Generative AI and Machine Learning Collaboration for Container Dwell Time Prediction via Data Standardization
by: Kim, Minseop, et al.
Published: (2026)

Minimizing the Value-at-Risk of Loan Portfolio via Deep Neural Networks
by: Di Wang, Albert, et al.
Published: (2025)

Benchmarking Time Series Foundation Models for Short-Term Household Electricity Load Forecasting
by: Meyer, Marcel, et al.
Published: (2024)

Leveraging Time Series Categorization and Temporal Fusion Transformers to Improve Cryptocurrency Price Forecasting
by: Peik, Arash, et al.
Published: (2024)

Internet sentiment exacerbates intraday overtrading, evidence from A-Share market
by: Yifeng, Peng
Published: (2024)

Toward Black Scholes for Prediction Markets: A Unified Kernel and Market Maker's Handbook
by: Dalen, Shaw
Published: (2025)

Application of Tensor Neural Networks to Pricing Bermudan Swaptions
by: Patel, Raj G., et al.
Published: (2023)

A Roadmap for Applying Graph Neural Networks to Numerical Data: Insights from Cementitious Materials
by: Sharmin, Mahmuda, et al.
Published: (2025)

EXFormer: A Multi-Scale Trend-Aware Transformer with Dynamic Variable Selection for Foreign Exchange Returns Prediction
by: Liu, Dinggao, et al.
Published: (2025)

Channel, Trend and Periodic-Wise Representation Learning for Multivariate Long-term Time Series Forecasting
by: Song, Zhangyao, et al.
Published: (2025)

Impacts of Economic Policies on Wealth Distribution in Token Economies
by: Sadykhov, Rem, et al.
Published: (2026)

Integrated Finite Element Neural Network (IFENN) for Phase-Field Fracture with Minimal Input and Generalized Geometry-Load Handling
by: Pantidis, Panos, et al.
Published: (2025)

Decentralized Token Economy Theory (DeTEcT)
by: Sadykhov, Rem, et al.
Published: (2023)

Identifying and Quantifying Financial Bubbles with the Hyped Log-Periodic Power Law Model
by: Cao, Zheng, et al.
Published: (2025)

DeTEcT: Dynamic and Probabilistic Parameters Extension
by: Sadykhov, Rem, et al.
Published: (2024)