This repository aggregates state-of-the-art research papers on deep learning for time series forecasting, along with associated code implementations and datasets. It covers classic methods versus deep learning approaches, includes references to models like Autoformer, LSTM, N-BEATS, and Diffusion models for time series, and references forecasting competitions and benchmark datasets. The repository serves as a knowledge hub for practitioners and researchers working on time series prediction tasks.