:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Lassen, Oskar Bohn, Agriesti, Serio, Eldafrawi, Mohamed, Gammelli, Daniele, Cantelmo, Guido, Gentile, Guido, Pereira, Francisco Camara
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2505.11230
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Metalearning traffic assignment for network disruptions with graph convolutional neural networks
di: Agriesti, Serio, et al.
Pubblicazione: (2026)

Learning to Learn the Macroscopic Fundamental Diagram using Physics-Informed and meta Machine Learning techniques
di: Roark, Amalie, et al.
Pubblicazione: (2025)

Climate Surrogates for Scalable Multi-Agent Reinforcement Learning: A Case Study with CICERO-SCM
di: Lassen, Oskar Bohn, et al.
Pubblicazione: (2025)

GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding
di: Gaber, Johannes, et al.
Pubblicazione: (2025)

An equilibrium-seeking search algorithm for integrating large-scale activity-based and dynamic traffic assignment models
di: Agriesti, Serio, et al.
Pubblicazione: (2024)

End-to-End Heterogeneous Graph Neural Networks for Traffic Assignment
di: Liu, Tong, et al.
Pubblicazione: (2023)

Heterogeneous Graph Sequence Neural Networks for Dynamic Traffic Assignment
di: Liu, Tong, et al.
Pubblicazione: (2024)

A Bayesian Optimization approach for calibrating large-scale activity-based transport models
di: Agriesti, Serio, et al.
Pubblicazione: (2023)

Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning
di: Singhal, Aaryan, et al.
Pubblicazione: (2023)

Implicit Bias of Mirror Flow in Homogeneous Neural Networks: Sparse and Dense Feature Learning
di: Jacobs, Tom, et al.
Pubblicazione: (2026)

Competitive Multi-Operator Reinforcement Learning for Joint Pricing and Fleet Rebalancing in AMoD Systems
di: Toft, Emil Kragh, et al.
Pubblicazione: (2026)

Offline Hierarchical Reinforcement Learning via Inverse Optimization
di: Schmidt, Carolin, et al.
Pubblicazione: (2024)

Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression
di: Liang, Shuang, et al.
Pubblicazione: (2024)

Enabling On-device Continual Learning with Binary Neural Networks
di: Vorabbi, Lorenzo, et al.
Pubblicazione: (2024)

Robustness Verification of Polynomial Neural Networks
di: Alexandr, Yulia, et al.
Pubblicazione: (2026)

Multi-Class Traffic Assignment using Multi-View Heterogeneous Graph Attention Networks
di: Liu, Tong, et al.
Pubblicazione: (2025)

Understanding Learning Invariance in Deep Linear Networks
di: Duan, Hao, et al.
Pubblicazione: (2025)

Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting
di: Lee, Sanghyun, et al.
Pubblicazione: (2024)

Territorialismo e a política de desenvolvimento: estratégias de produção do território no Brasil
di: Weslley Cantelmo
Pubblicazione: (2015)

Território e territorialismo: a abrangência conceitual e a noção de poder
di: Weslley Cantelmo
Pubblicazione: (2015)

Learning to Simulate: Generative Metamodeling via Quantile Regression
di: Hong, L. Jeff, et al.
Pubblicazione: (2023)

Pain Management in Mandibular Molars With Symptomatic Irreversible Pulpitis: Mechanisms, Clinical Efficacy and Current Evidence: A Narrative Review
di: S. Eldafrawi, et al.
Pubblicazione: (2026)

Understanding Pooling in Graph Neural Networks
di: Grattarola, Daniele, et al.
Pubblicazione: (2021)

Robo-taxi Fleet Coordination at Scale via Reinforcement Learning
di: Tresca, Luigi, et al.
Pubblicazione: (2025)

Synchronization and averaging in partially hyperbolic systems with fast and slow variables
di: Bonetto, Federico, et al.
Pubblicazione: (2024)

Scalable and Reliable Multi-agent Reinforcement Learning for Traffic Assignment
di: Wang, Leizhen, et al.
Pubblicazione: (2025)

SpaPool: Soft Partition Assignment Pooling for__Graph Neural Networks
di: Govan, Rodrigue, et al.
Pubblicazione: (2025)

On the Local Complexity of Linear Regions in Deep ReLU Networks
di: Patel, Niket, et al.
Pubblicazione: (2024)

Machine-Learned Prediction Equilibrium for Dynamic Traffic Assignment
di: Graf, Lukas, et al.
Pubblicazione: (2021)

Sensitivity analysis using the Metamodel of Optimal Prognosis
di: Most, Thomas, et al.
Pubblicazione: (2024)

Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting
di: Ghaffari, Amirhossein, et al.
Pubblicazione: (2026)

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

Balanced Multimodal Learning via Mutual Information
di: Xie, Rongrong, et al.
Pubblicazione: (2025)

The Real Tropical Geometry of Neural Networks
di: Brandenburg, Marie-Charlotte, et al.
Pubblicazione: (2024)

Predicting Traffic Flow with Federated Learning and Graph Neural with Asynchronous Computations Network
di: Yaqub, Muhammad, et al.
Pubblicazione: (2024)

Variable Assignment Invariant Neural Networks for Learning Logic Programs
di: Phua, Yin Jun, et al.
Pubblicazione: (2024)

Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks
di: Zhou, Fangtong, et al.
Pubblicazione: (2025)

Bayesian Active Learning for Censored Regression
di: Hüttel, Frederik Boe, et al.
Pubblicazione: (2024)

MHGNet: Multi-Heterogeneous Graph Neural Network for Traffic Prediction
di: Wu, Mei, et al.
Pubblicazione: (2025)

Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling
di: Bianchi, Filippo Maria, et al.
Pubblicazione: (2019)