:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Sheng, Zhi, Yuan, Yuan, Zhang, Guozhen, Li, Yong
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.15961
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Collaborative Deterministic-Probabilistic Forecasting for Diverse Spatiotemporal Systems
by: Sheng, Zhi, et al.
Published: (2025)

Weather Maps as Tokens: Transformers for Renewable Energy Forecasting
by: Battini, Federico
Published: (2025)

Budget-constrained Collaborative Renewable Energy Forecasting Market
by: Goncalves, Carla, et al.
Published: (2025)

Benchmarks and Custom Package for Energy Forecasting
by: Wang, Zhixian, et al.
Published: (2023)

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting
by: Kleinebrahm, Max, et al.
Published: (2026)

Improving Sequential Market Coordination via Value-oriented Renewable Energy Forecasting
by: Zhang, Yufan, et al.
Published: (2024)

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

LTPNet Integration of Deep Learning and Environmental Decision Support Systems for Renewable Energy Demand Forecasting
by: Li, Te, et al.
Published: (2024)

Multivariate LSTM-Based Forecasting for Renewable Energy: Enhancing Climate Change Mitigation
by: Kamrani, Farshid, et al.
Published: (2026)

Diffusion Transformers as Open-World Spatiotemporal Foundation Models
by: Yuan, Yuan, et al.
Published: (2024)

A Hybrid Autoencoder-Transformer Model for Robust Day-Ahead Electricity Price Forecasting under Extreme Conditions
by: Tang, Boyan, et al.
Published: (2025)

Efficient Deterministic Renewable Energy Forecasting Guided by Multiple-Location Weather Data
by: Symeonidis, Charalampos, et al.
Published: (2024)

Copula-Based Aggregation and Context-Aware Conformal Prediction for Reliable Renewable Energy Forecasting
by: Moradi, Alireza, et al.
Published: (2026)

Load and Renewable Energy Forecasting Using Deep Learning for Grid Stability
by: Sarkar, Kamal
Published: (2025)

Unveiling the Power of Noise Priors: Enhancing Diffusion Models for Mobile Traffic Prediction
by: Sheng, Zhi, et al.
Published: (2025)

CT-PatchTST: Channel-Time Patch Time-Series Transformer for Long-Term Renewable Energy Forecasting
by: Lu, Kuan, et al.
Published: (2025)

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data
by: Liang, Daojun, et al.
Published: (2024)

UniFlow: A Foundation Model for Unified Urban Spatio-Temporal Flow Prediction
by: Yuan, Yuan, et al.
Published: (2024)

Towards Accurate Forecasting of Renewable Energy : Building Datasets and Benchmarking Machine Learning Models for Solar and Wind Power in France
by: Lindas, Eloi, et al.
Published: (2025)

Deep Learning in Renewable Energy Forecasting: A Cross-Dataset Evaluation of Temporal and Spatial Models
by: Sua, Lutfu, et al.
Published: (2025)

RE-LLM: Integrating Large Language Models into Renewable Energy Systems
by: Forootani, Ali, et al.
Published: (2025)

FreeGNN: Continual Source-Free Graph Neural Network Adaptation for Renewable Energy Forecasting
by: Bahi, Abderaouf, et al.
Published: (2026)

Robust Learning of Diffusion Models with Extremely Noisy Conditions
by: Chen, Xin, et al.
Published: (2025)

Progressive Supervision via Label Decomposition: An Long-Term and Large-Scale Wireless Traffic Forecasting Method
by: Liang, Daojun, et al.
Published: (2025)

Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
by: Feng, Wanjin, et al.
Published: (2025)

Resilient Load Forecasting under Climate Change: Adaptive Conditional Neural Processes for Few-Shot Extreme Load Forecasting
by: Hu, Chenxi, et al.
Published: (2026)

RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges
by: Li, Ruize, et al.
Published: (2026)

Explainable Earth Surface Forecasting under Extreme Events
by: Pellicer-Valero, Oscar J., et al.
Published: (2024)

ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
by: Zhang, Jiawen, et al.
Published: (2023)

A Data-driven Dynamic Temporal Correlation Modeling Framework for Renewable Energy Scenario Generation
by: Dong, Xiaochong, et al.
Published: (2025)

ECTO: Exogenous-Conditioned Temporal Operator for Ultra-Short-Term Wind Power Forecasting
by: Yuan, Cao, et al.
Published: (2026)

LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting
by: Chuang, Yu-Neng, et al.
Published: (2024)

AdaMixT: Adaptive Weighted Mixture of Multi-Scale Expert Transformers for Time Series Forecasting
by: Zhang, Huanyao, et al.
Published: (2025)

Integrated Forecasting of Marine Renewable Power: An Adaptively Bayesian-Optimized MVMD-LSTM Framework for Wind-Solar-Wave Energy
by: Xie, Baoyi, et al.
Published: (2025)

OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
by: Li, Lin, et al.
Published: (2023)

Transformers as Intrinsic Optimizers: Forward Inference through the Energy Principle
by: Ren, Ruifeng, et al.
Published: (2025)

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types
by: Danish, Muhammad Umair, et al.
Published: (2025)

Efficient Extreme Operating Condition Search for Online Relay Setting Calculation in Renewable Power Systems Based on Parallel Graph Neural Network
by: Li, Yan, et al.
Published: (2025)

StrEBM: A Structured Latent Energy-Based Model for Blind Source Separation
by: Wei, Yuan-Hao
Published: (2026)

SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting
by: Minnick, John R., et al.
Published: (2026)