:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Moretti, Davide, Onofri, Elia, Cristiani, Emiliano
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning 90B20, 62M10
Accès en ligne:	https://arxiv.org/abs/2504.00881
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data
par: Xu, Zexing, et autres
Publié: (2024)

Robust and Heterogenous Odds Ratio: Estimating Price Sensitivity for Unbought Items
par: Pauphilet, Jean
Publié: (2021)

City-Conditioned Memory for Multi-City Traffic and Mobility Forecasting
par: Du, Wenzhang
Publié: (2025)

Statistical and Machine Learning Analysis of Traffic Accidents on US 158 in Currituck County: A Comparison with HSM Predictions
par: Sawyer, Jennifer, et autres
Publié: (2025)

Mini-Batch Covariance, Diffusion Limits, and Oracle Complexity in Stochastic Gradient Descent: A Sampling-Design Perspective
par: Zantedeschi, Daniel, et autres
Publié: (2026)

On a Reinforcement Learning Methodology for Epidemic Control, with application to COVID-19
par: Iannucci, Giacomo, et autres
Publié: (2025)

Opening the Black Box: Nowcasting Singapore's GDP Growth and its Explainability
par: Attolico, Luca
Publié: (2025)

Predicting Graph Structure via Adapted Flux Balance Analysis
par: Kandanaarachchi, Sevvandi, et autres
Publié: (2025)

Optimal Learning via Moderate Deviations Theory
par: Ganguly, Arnab, et autres
Publié: (2023)

Robust volatility updates for Hierarchical Gaussian Filtering
par: Mathys, Christoph, et autres
Publié: (2026)

A Statistical Framework for Model Selection in LSTM Networks
par: Mostafa, Fahad
Publié: (2025)

Causal-Audit: A Framework for Risk Assessment of Assumption Violations in Time-Series Causal Discovery
par: Ruiz, Marco, et autres
Publié: (2026)

Nonstationary Distribution Estimation via Wasserstein Probability Flows
par: Anderson, Edward J., et autres
Publié: (2025)

Evaluating utility in synthetic banking microdata applications
par: Caceres, Hugo E., et autres
Publié: (2024)

Double Descent and Benign Overfitting in Macroeconomic Forecasting
par: Carriero, Andrea, et autres
Publié: (2026)

Less is More: Strategic Expert Selection Outperforms Ensemble Complexity in Traffic Forecasting
par: Guettala, Walid, et autres
Publié: (2025)

Empirical Mode Decomposition and Graph Transformation of the MSCI World Index: A Multiscale Topological Analysis for Graph Neural Network Modeling
par: Riscos, Agustín M. de los, et autres
Publié: (2025)

Stochastic Predictive Analytics for Stocks in the Newsvendor Problem
par: Pury, Pedro A.
Publié: (2025)

Queue up for takeoff: a transferable deep learning framework for flight delay prediction
par: Aghanya, Nnamdi Daniel, et autres
Publié: (2025)

Nowcasting using regression on signatures
par: Cohen, Samuel N., et autres
Publié: (2023)

Electricity Price Prediction Using Multi-Kernel Gaussian Process Regression Combined with Kernel-Based Support Vector Regression
par: Das, Abhinav, et autres
Publié: (2024)

How to measure the uncertainty of a tournament draw: The case of European football's Champions League
par: Csató, László, et autres
Publié: (2025)

Bayesian Multi-Topology Express Transportation Network Design under Posterior Predictive Demand, Sorting-Efficiency and Delivery-Time Uncertainty
par: Chatterjee, Debashis
Publié: (2026)

Forecasting Geopolitical Events with a Sparse Temporal Fusion Transformer and Gaussian Process Hybrid: A Case Study in Middle Eastern and U.S. Conflict Dynamics
par: Huang, Hsin-Hsiung, et autres
Publié: (2025)

Minimization of Functions on Dually Flat Spaces Using Geodesic Descent Based on Dual Connections
par: Omiya, Gaku, et autres
Publié: (2025)

The Aligned Economic Index & The State Switching Model
par: Aarab, Ilias
Publié: (2025)

A hidden benefit of incomplete round-robin tournaments: Encouraging offensive play
par: Csató, László
Publié: (2025)

Testing Conditional Mean Independence Using Generative Neural Networks
par: Zhang, Yi, et autres
Publié: (2025)

Optimal Contextual Pricing under Agnostic Non-Lipschitz Demand
par: Xu, Jianyu, et autres
Publié: (2026)

Comparative Analysis of Time Series Foundation Models for Demographic Forecasting: Enhancing Predictive Accuracy in US Population Dynamics
par: Akella, Aditya, et autres
Publié: (2025)

Consistent line clustering using geometric hypergraphs
par: Alaluusua, Kalle, et autres
Publié: (2025)

grangersearch: An R Package for Exhaustive Granger Causality Testing with Tidyverse Integration
par: Korfiatis, Nikolaos
Publié: (2026)

Inverting the Fundamental Diagram and Forecasting Boundary Conditions: How Machine Learning Can Improve Macroscopic Models for Traffic Flow
par: Briani, Maya, et autres
Publié: (2023)

CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering
par: Degen, Isabella, et autres
Publié: (2025)

Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation
par: Lee, Ho Ming, et autres
Publié: (2025)

The Economics of AI Inference: Inflation Dynamics, Welfare Costs, and Optimal Monetary Policy under the Inference-Cost Phillips Curve
par: Lundström-Imanov, Gustav Olaf Yunus Laitinen-Fredriksson
Publié: (2026)

Generalised envelope spectrum-based signal-to-noise objectives: Formulation, optimisation and application for gear fault detection under time-varying speed conditions
par: Schmidt, Stephan, et autres
Publié: (2024)

Nonparametric Vector Quantile Autoregression
par: González-Sanz, Alberto, et autres
Publié: (2025)

On a class of multiplicative Lindley-type recursions with Markov-modulated dependencies
par: Dimitriou, Ioannis
Publié: (2025)

On Markov-dependent reflected autoregressive processes and related models
par: Dimitriou, Ioannis
Publié: (2024)