Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
In each of the past three regular seasons, exactly 17 pitchers made at least one start for the Dodgers. This underscores something we all know: you can never have too much pitching because pitching ...
Real-world time series often exhibit a non-stationary nature, degrading the performance of pre-trained forecasting models. Test-Time Adaptation (TTA) addresses this by adjusting models during ...
Abstract: With the proliferation of multimodal data in real-world applications, integrating time series with auxiliary modalities has become critical for accurate forecasting. Although Transformers ...
This project is sponsored by Z.ai, supporting us with their GLM CODING PLAN.GLM CODING PLAN is a subscription service designed for AI coding, starting at just $3/month. It provides access to their ...
This study reviews the advancements in AI-driven methods for predicting stock prices, tracing their evolution from traditional approaches to modern finance. The role of AI in the market extends beyond ...
A Multi-Task End-to-End Multivariate Long-Sequence Time Series Prediction Model for Load Forecasting
Abstract: With the increasing complexity of the power system, and the growing global demand for electricity, accurate and effective forecasting of electricity load, electricity prices, and related ...
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