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Found 5 papers, 0 papers with code
Stock Market Sentiment Classification and Backtesting via Fine-tuned BERT
Subsequently, based on the above model, the user comment data crawled is labeled with emotional polarity, and the obtained label information is combined with the Alpha191 model to participate in regression, and significant regression results are obtained.
Bi-LSTM Price Prediction based on Attention Mechanism
In this paper, we propose a bidirectional LSTM neural network based on an attention mechanism, which is based on two popular assets, gold and bitcoin.
A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks
More and more stock trading strategies are constructed using deep reinforcement learning (DRL) algorithms, but DRL methods originally widely used in the gaming community are not directly adaptable to financial data with low signal-to-noise ratios and unevenness, and thus suffer from performance shortcomings.
Reconstruction of gene regulatory network via sparse optimization
In this paper, we tested several sparse optimization algorithms based on the public dataset of the DREAM5 Gene Regulatory Network Inference Challenge.
Palm Vein Recognition via Multi-task Loss Function and Attention Layer
With the improvement of arithmetic power and algorithm accuracy of personal devices, biological features are increasingly widely used in personal identification, and palm vein recognition has rich extractable features and has been widely studied in recent years.
