:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Immordino, Gabriele, Vaiuso, Andrea, Da Ronch, Andrea, Righi, Marcello
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Computational Engineering, Finance, and Science
Accesso online:	https://arxiv.org/abs/2411.11592
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Predicting Transonic Flowfields in Non-Homogeneous Unstructured Grids Using Autoencoder Graph Convolutional Networks
di: Immordino, Gabriele, et al.
Pubblicazione: (2024)

Multi-Fidelity Bayesian Neural Network for Uncertainty Quantification in Transonic Aerodynamic Loads
di: Vaiuso, Andrea, et al.
Pubblicazione: (2024)

Parametric Nonlinear Volterra Series via Machine Learning: Transonic Aerodynamics
di: Immordino, Gabriele, et al.
Pubblicazione: (2024)

A Retrieval-Augmented Language Assistant for Unmanned Aircraft Safety Assessment and Regulatory Compliance
di: Immordino, Gabriele, et al.
Pubblicazione: (2026)

Drone Acoustic Analysis for Predicting Psychoacoustic Annoyance via Artificial Neural Networks
di: Vaiuso, Andrea, et al.
Pubblicazione: (2024)

Dynami-CAL GraphNet: A Physics-Informed Graph Neural Network Conserving Linear and Angular Momentum for Dynamical Systems
di: Sharma, Vinay, et al.
Pubblicazione: (2025)

Equi-Euler GraphNet: An Equivariant, Temporal-Dynamics Informed Graph Neural Network for Dual Force and Trajectory Prediction in Multi-Body Systems
di: Sharma, Vinay, et al.
Pubblicazione: (2025)

Scale-Equivariant Generative Forecasting: Weight-Tied Dilated Convolutions, Wavelet Scattering Inputs, and Spectral-Consistency Training for Self-Similar Time Series
di: Morandi, Andrea
Pubblicazione: (2026)

Spatio-Temporal Attention Graph Neural Network: Explaining Causalities With Attention
di: Koistinen, Kosti, et al.
Pubblicazione: (2026)

Going with the Speed of Sound: Pushing Neural Surrogates into Highly-turbulent Transonic Regimes
di: Paischer, Fabian, et al.
Pubblicazione: (2025)

CiRL: Open-Source Environments for Reinforcement Learning in Circular Economy and Net Zero
di: Zocco, Federico, et al.
Pubblicazione: (2025)

Counterfactual Forecasting of Human Behavior using Generative AI and Causal Graphs
di: Uddandarao, Dharmateja Priyadarshi, et al.
Pubblicazione: (2025)

CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting
di: Wan, Shu, et al.
Pubblicazione: (2025)

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

Synthetic Pattern Generation and Detection of Financial Activities using Graph Autoencoders
di: Zola, Francesco, et al.
Pubblicazione: (2026)

Computational Fluid Dynamics Optimization of F1 Front Wing using Physics Informed Neural Networks
di: Shah, Naval
Pubblicazione: (2025)

MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations
di: Deshpande, Saurabh, et al.
Pubblicazione: (2022)

Efficient Traffic Prediction Through Spatio-Temporal Distillation
di: Zhang, Qianru, et al.
Pubblicazione: (2025)

LatticeGraphNet: A two-scale graph neural operator for simulating lattice structures
di: Jain, Ayush, et al.
Pubblicazione: (2024)

UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate Prediction
di: Xin, Weilin, et al.
Pubblicazione: (2025)

An Attention-based Spatio-Temporal Neural Operator for Evolving Physics
di: Karkaria, Vispi, et al.
Pubblicazione: (2025)

Crisis-Resilient Portfolio Management via Graph-based Spatio-Temporal Learning
di: Li, Zan, et al.
Pubblicazione: (2025)

A Graph Machine Learning Approach for Detecting Topological Patterns in Transactional Graphs
di: Zola, Francesco, et al.
Pubblicazione: (2025)

Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems
di: Wolf, Florian, et al.
Pubblicazione: (2024)

Large and Deep Factor Models
di: Kelly, Bryan, et al.
Pubblicazione: (2024)

Temperature Distribution Prediction in Laser Powder Bed Fusion using Transferable and Scalable Graph Neural Networks
di: Raut, Riddhiman, et al.
Pubblicazione: (2024)

Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction
di: Zhang, Zeyang, et al.
Pubblicazione: (2023)

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

A Machine Learning Approach For Bitcoin Forecasting
di: Sossi-Rojas, Stefano, et al.
Pubblicazione: (2025)

Multi-Objective Reinforcement Learning-based Approach for Pressurized Water Reactor Optimization
di: Seurin, Paul, et al.
Pubblicazione: (2023)

GeOT: A spatially explicit framework for evaluating spatio-temporal predictions
di: Wiedemann, Nina, et al.
Pubblicazione: (2024)

ResNLS: An Improved Model for Stock Price Forecasting
di: Jia, Yuanzhe, et al.
Pubblicazione: (2023)

Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns
di: De Rosa, Pasquale, et al.
Pubblicazione: (2024)

A Novel Decision Ensemble Framework: Customized Attention-BiLSTM and XGBoost for Speculative Stock Price Forecasting
di: Din, Riaz Ud, et al.
Pubblicazione: (2024)

Hidformer: Transformer-Style Neural Network in Stock Price Forecasting
di: Szydłowski, Kamil Ł., et al.
Pubblicazione: (2024)

STAResNet: a Network in Spacetime Algebra to solve Maxwell's PDEs
di: Pepe, Alberto, et al.
Pubblicazione: (2024)

Semantic-Enhanced Time-Series Forecasting via Large Language Models
di: Liu, Hao, et al.
Pubblicazione: (2025)

FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting
di: Hu, Yifan, et al.
Pubblicazione: (2025)

FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics
di: Li, Pingzhi, et al.
Pubblicazione: (2026)

Privacy-Preserving Generation Fraud Detection for Distributed Photovoltaic Systems: A Solar Irradiance-Fused Federated Learning Framework
di: Chen, Xiaolu, et al.
Pubblicazione: (2026)