repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · yesterday
aeon-toolkit/aeon
A toolkit for time series machine learning and deep learning
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 51%LeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation Learning →
- PossiblePossibly related (embedding) · 50%How Good Can Linear Models Be for Time-Series Forecasting? →
- PossiblePossibly related (embedding) · 47%Forecasting With LLMs: Improved Generalization Through Feature Steering →
- PossiblePossibly related (embedding) · 47%A Lightweight Self-Supervised Learning Framework for Multivariate Time Series using Hierarchical-JEPA on ECG Data →
- PossiblePossibly related (embedding) · 51%Best machine learning development companies for time series forecasting (2026) - PC Tech Magazine →
- PossiblePossibly related (embedding) · 53%GatedLinear: Adaptive Routing of Complementary Linear Bases for Time Series Forecasting →
- PossiblePossibly related (embedding) · 46%Dynamic rough set learning for reliable early warning in industrial time-series systems - Nature →
Implements
paperLeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation LearningpaperHow Good Can Linear Models Be for Time-Series Forecasting?paperForecasting With LLMs: Improved Generalization Through Feature SteeringpaperA Lightweight Self-Supervised Learning Framework for Multivariate Time Series using Hierarchical-JEPA on ECG Data
Covers (incoming)
Implements (incoming)
Related across the graph
newsBest machine learning development companies for time series forecasting (2026) - PC Tech MagazinepaperGatedLinear: Adaptive Routing of Complementary Linear Bases for Time Series ForecastingpaperLeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation LearningpaperHow Good Can Linear Models Be for Time-Series Forecasting?paperA Lightweight Self-Supervised Learning Framework for Multivariate Time Series using Hierarchical-JEPA on ECG DatanewsDynamic rough set learning for reliable early warning in industrial time-series systems - NaturepaperForecasting With LLMs: Improved Generalization Through Feature Steering