DRIO adds worst-case Wasserstein regularization to time series imputation, yielding a tractable adversarial surrogate and alternating algorithm that improves robustness under missingness.
Cnnpred: Cnn-based stock market prediction using a diverse set of variables.Expert Systems with Applications, 129:273–285
2 Pith papers cite this work. Polarity classification is still indexing.
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Hybrid LSTM-QCBM model outperforms classical LSTM on SSE Composite and CSI 300 volatility forecasting and supports quantum-assisted training followed by fully classical inference.
citing papers explorer
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Multivariate Time Series Data Imputation via Distributionally Robust Regularization
DRIO adds worst-case Wasserstein regularization to time series imputation, yielding a tractable adversarial surrogate and alternating algorithm that improves robustness under missingness.
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A Hybrid Quantum-Classical Framework for Financial Volatility Forecasting Based on Quantum Circuit Born Machines
Hybrid LSTM-QCBM model outperforms classical LSTM on SSE Composite and CSI 300 volatility forecasting and supports quantum-assisted training followed by fully classical inference.