Image de couverture de livre

Granger Causality using Neural Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sultan, Malik Shahid, Horvath, Samuel, Ombao, Hernando
Format:	Preprint
Publié:	2022
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

Emergent Granger Causality in Neural Networks: Can Prediction Alone Reveal Structure?
par: Sultan, Malik Shahid, et autres
Publié: (2025)

Classification of High-dimensional Time Series in Spectral Domain using Explainable Features
par: Roy, Sarbojit, et autres
Publié: (2024)

Granger Causality in High-Dimensional Networks of Time Series
par: Aslan, Sipan, et autres
Publié: (2024)

Statistical Inference for Local Granger Causality
par: Liu, Yan, et autres
Publié: (2021)

Jacobian Regularizer-based Neural Granger Causality
par: Zhou, Wanqi, et autres
Publié: (2024)

Granger Causality Detection with Kolmogorov-Arnold Networks
par: Lin, Hongyu, et autres
Publié: (2024)

Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
par: Adedayo, S. A.
Publié: (2025)

Transformers with Sparse Attention for Granger Causality
par: Mahesh, Riya, et autres
Publié: (2024)

Kolmogorov-Arnold Networks for Time Series Granger Causality Inference
par: Liu, Meiliang, et autres
Publié: (2025)

Predictive Performance Test based on the Exhaustive Nested Cross-Validation for High-dimensional data
par: Gauran, Iris Ivy, et autres
Publié: (2024)

Towards Uncertainty-Aware Federated Granger Causal Learning
par: Mohanty, Ayush, et autres
Publié: (2026)

Granger Causality in Extremes
par: Bodik, Juraj, et autres
Publié: (2024)

CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis
par: Zheng, Kaizhong, et autres
Publié: (2023)

A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity
par: Lin, Jiahe, et autres
Publié: (2024)

A Granger-Causal Perspective on Gradient Descent with Application to Pruning
par: Shah, Aditya, et autres
Publié: (2024)

Constraint- and Score-Based Nonlinear Granger Causality Discovery with Kernels
par: Murphy, Fiona, et autres
Publié: (2026)

Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
par: Zhao, He, et autres
Publié: (2024)

Canonical Tail Dependence for Soft Extremal Clustering of Multichannel Brain Signals
par: Talento, Mara Sherlin, et autres
Publié: (2025)

Root Cause Analysis In Microservice Using Neural Granger Causal Discovery
par: Lin, Cheng-Ming, et autres
Publié: (2024)

Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data
par: Poonia, Harsh, et autres
Publié: (2025)

Federated Granger Causality Learning for Interdependent Clients with State Space Representation
par: Mohanty, Ayush, et autres
Publié: (2025)

Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length
par: Hlavackova-Schindler, Katerina, et autres
Publié: (2023)

Robust fuzzy clustering for high-dimensional multivariate time series with outlier detection
par: Ma, Ziling, et autres
Publié: (2025)

Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
par: Ma, Ziling, et autres
Publié: (2026)

GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Imaging Studies
par: Nguyen, Minh, et autres
Publié: (2022)

Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations
par: Nguyen, Linh, et autres
Publié: (2025)

Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes
par: Wu, Dongxia, et autres
Publié: (2024)

FCPCA: Fuzzy clustering of high-dimensional time series based on common principal component analysis
par: Ma, Ziling, et autres
Publié: (2025)

Robust Spectral Fuzzy Clustering of Multivariate Time Series with Applications to Electroencephalogram
par: Ma, Ziling, et autres
Publié: (2025)

TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences
par: Liu, Yuequn, et autres
Publié: (2023)

From News to Returns: A Granger-Causal Hypergraph Transformer on the Sphere
par: Harit, Anoushka, et autres
Publié: (2025)

Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data
par: Zhang, Ziyi, et autres
Publié: (2024)

Nonlinear Causality in Time Series Networks: With Application to Motor Imagery vs Execution
par: Aslan, Sipan, et autres
Publié: (2024)

InvarGC: Invariant Granger Causality for Heterogeneous Interventional Time Series under Latent Confounding
par: Zhang, Ziyi, et autres
Publié: (2025)

EEG-MSAF: An Interpretable Microstate Framework uncovers Default-Mode Decoherence in Early Neurodegeneration
par: Hasan, Mohammad Mehedi, et autres
Publié: (2025)

Stationary Processes, Wiener-Granger Causality, and Matrix Spectral Factorization
par: Ephremidze, Lasha
Publié: (2024)

Vanishing Feature: Diagnosing Model Merging and Beyond
par: Qu, Xingyu, et autres
Publié: (2024)

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
par: Tastan, Nurbek, et autres
Publié: (2025)

Multi-Band Variable-Lag Granger Causality: A Unified Framework for Causal Time Series Inference across Frequencies
par: Sookkongwaree, Chakattrai, et autres
Publié: (2025)

Can Muon Fine-tune Adam-Pretrained Models?
par: Qu, Xingyu, et autres
Publié: (2026)