<ul><li>The accuracy of cryptocurrency price prediction is vital for organizing and managing portfolios and making transactions.</li><li>To improve accuracy, this study categorizes financial time series into similar subseries.</li><li>Deep learning models with attention mechanisms are created for each subseries category to predict future steps.</li><li>To overcome limited training data, the study suggests combining time series data from multiple cryptocurrencies.</li></ul>

Leveraging Time Series Categorization and Temporal Fusion Transformers to Improve Cryptocurrency Price Forecasting

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