Yes, Transformers are Effective for Time Series Forecasting (+ Autoformer)

Probabilistic Time Series Forecasting with 🤗 Transformers

A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods

arXiv:2607. 15705v1 Announce Type: new Abstract: Accurate load forecasting at multiple grid levels is essential for future smart grids, ranging from aggregated control area forecasts for balancing supply and demand to forecasts of individual end-consumer loads for demand-side management and energy management systems.

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting

arXiv:2607. 22299v1 Announce Type: cross Abstract: Forecasting multiple time-series with high-dimensional covariates presents a core challenge: unifying common temporal patterns while retaining meaningful series-specific information.

Introducing Optimum: The Optimization Toolkit for Transformers at Scale

AROpt: An Optimization Method for Autoregressive Time Series Forecasting

arXiv:2602. 02288v3 Announce Type: replace Abstract: Current time-series forecasting models are primarily based on transformer-style neural networks.

Timm ❤️ Transformers: Use any timm model with transformers

Extreme Adaptive Transformer for Time Series Forecasting

arXiv:2607. 02437v1 Announce Type: new Abstract: Time series forecasting remains challenging when the underlying data contain rare but critical extreme events.

Patch Time Series Transformer in Hugging Face

Mixture of Experts (MoEs) in Transformers

Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations

arXiv:2608. 13260v1 Announce Type: new Abstract: Accurate modeling and forecasting of power transformer thermal behavior are critical for reliability, asset lifetime, and optimized power system operation.

The State-Prediction Separation Hypothesis

arXiv:2607. 01218v1 Announce Type: cross Abstract: Transformers use the same forward computation stream to both predict the next token and store useful state for future token predictions.

Differential Transformer V2