Research & Innovations

Key Contributions

• Developed novel domain-generalization approach integrating RNN with Latent Variable Autoregressive Models
• Improved risk prediction accuracy through feature knowledge adaptation
• Applied dropout, L2 regularization, and Bayesian optimization techniques
• View Paper: Anomaly Detection in Financial Time Series Based on Recurrent Neural Networks and Latent Variable Autoregressive Models
• View Notification of Acceptance of Paper: 论文录用通知