So far, running LLMs has required a large amount of computing resources, mainly GPUs. Running locally, a simple prompt with a typical LLM takes on an average Mac ...

A full-stack inflation-forecasting toolkit that pairs classical ARIMA diagnostics in Stata with an LSTM pipeline in Python. The project walks from raw CPI data ingestion and exploratory visualisation ...

Abstract: Power load forecasting is the foundation of maintaining power grid stability, and can assist in decision-making to reduce operating costs. Fine-grained long sequence load forecasting ...

Abstract: A recent study showcased the efficacy of Long Short-Term Memory (LSTM) in significantly reducing average indoor localization Root Mean Square Error (RMSE ...