Cover Image

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ahmad, Owais, Ramezankhani, Milad, Deodhar, Anirudh
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
by: Ramezankhani, Milad, et al.
Published: (2025)

An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study
by: Ramezankhani, Milad, et al.
Published: (2024)

Accelerated Gradient-based Design Optimization Via Differentiable Physics-Informed Neural Operator: A Composites Autoclave Processing Case Study
by: Patel, Janak M., et al.
Published: (2025)

State of Health Estimation of Batteries Using a Time-Informed Dynamic Sequence-Inverted Transformer
by: Patel, Janak M., et al.
Published: (2025)

FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition
by: Ramezankhani, Milad, et al.
Published: (2024)

CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting
by: Näf, Jeffrey, et al.
Published: (2026)

Long-Term Probabilistic Forecast of Vegetation Conditions Using Climate Attributes in the Four Corners Region
by: McPhillips, Erika, et al.
Published: (2026)

Adaptive Bayesian Very Short-Term Wind Power Forecasting Based on the Generalised Logit Transformation
by: Shen, Tao, et al.
Published: (2025)

Long-Term Spatio-Temporal Forecasting of Monthly Rainfall in West Bengal Using Ensemble Learning Approaches
by: Adhikary, Jishu, et al.
Published: (2025)

Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approach
by: Pashmchi, Parastoo, et al.
Published: (2026)

Transportation Marketplace Rate Forecast Using Signature Transform
by: Gu, Haotian, et al.
Published: (2024)

Predicting the Skies: A Novel Model for Flight-Level Passenger Traffic Forecasting
by: Ehsani, Sina, et al.
Published: (2024)

A Composite-Loss Graph Neural Network for the Multivariate Post-Processing of Ensemble Weather Forecasts
by: Lakatos, Mária
Published: (2025)

Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
by: Moradi, Alireza, et al.
Published: (2025)

In-Context Learning Enhanced Credibility Transformer
by: Padayachy, Kishan, et al.
Published: (2025)

EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes
by: Stockman, Samuel, et al.
Published: (2024)

DemandLens: Enhancing Forecast Accuracy Through Product-Specific Hyperparameter Optimization
by: Pillai, Srijesh, et al.
Published: (2025)

Leveraging Knowledge Graphs and LLM Reasoning to Identify Operational Bottlenecks for Warehouse Planning Assistance
by: Parekh, Rishi, et al.
Published: (2025)

BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network
by: Liu, Yongzheng, et al.
Published: (2025)

Generative Probabilistic Time Series Forecasting and Applications in Grid Operations
by: Wang, Xinyi, et al.
Published: (2024)

Assessing the Operational Viability of Foundation Models for Time Series Forecasting
by: Soni, Kavin, et al.
Published: (2026)

Enhancing Global Maritime Traffic Network Forecasting with Gravity-Inspired Deep Learning Models
by: Song, Ruixin, et al.
Published: (2024)

Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood Risk
by: Pasche, Olivier C., et al.
Published: (2022)

Hybrid Pipeline SWD Detection in Long-Term EEG Signals
by: Rincon, Antonio Quintero, et al.
Published: (2025)

Feature Group Tabular Transformer: A Novel Approach to Traffic Crash Modeling and Causality Analysis
by: Lares, Oscar, et al.
Published: (2024)

Auto-Regressive Moving Diffusion Models for Time Series Forecasting
by: Gao, Jiaxin, et al.
Published: (2024)

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2025)

Federated Learning for Financial Forecasting
by: Noseda, Manuel, et al.
Published: (2025)

Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes
by: Wu, Fan, et al.
Published: (2023)

Data-driven Calibration Sample Selection and Forecast Combination in Electricity Price Forecasting: An Application of the ARHNN Method
by: Serafin, Tomasz, et al.
Published: (2025)

Forecasting Medium-Horizon Alzheimer's Disease Progression: Residual Gap-Aware Transformers for 24-Month CDR-SB Change from ADNI Clinical and Biomarker Histories
by: Tong, Ran, et al.
Published: (2026)

Wavelet-SARIMA-Transformer: A Hybrid Model for Rainfall Forecasting
by: Saikia, Junmoni, et al.
Published: (2025)

Simplifying Random Forests' Probabilistic Forecasts
by: Koster, Nils, et al.
Published: (2024)

Improving Geopolitical Forecasts with Bayesian Networks
by: Martin, Matthew
Published: (2026)

Modeling Headway in Heterogeneous and Mixed Traffic Flow: A Statistical Distribution Based on a General Exponential Function
by: Leungbootnak, Natchaphon, et al.
Published: (2025)

Mobility-based Traffic Forecasting in a Multimodal Transport System
by: Mboko, Henock M., et al.
Published: (2024)

Multi-task Neural Diffusion Processes
by: Rawson, Joseph, et al.
Published: (2025)

DiffKnock: Diffusion-based Knockoff Statistics for Neural Networks Inference
by: Ge, Heng, et al.
Published: (2025)

Adaptive Multi-task Learning for Probabilistic Load Forecasting
by: Zaballa, Onintze, et al.
Published: (2025)

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
by: S, Saranya Ganesh, et al.
Published: (2025)