5 papers
Trading Confidence: Comprehensive Uncertainty Estimation in Algorithmic Trading
Lin Li, Li Rong Wang, Hsuan Fu +1
Reinforcement Learning (RL) has emerged as a powerful approach in financial trading, enabling agents to learn optimal strategies through direct market interaction. However, financi…
Robust Uncertainty Estimation under Distribution Shift via Difference Reconstruction
Xinran Xu, Li Rong Wang, Xiuyi Fan
Estimating uncertainty in deep learning models is critical for reliable decision-making in high-stakes applications such as medical imaging. Prior research has established that the…
Explainable Melanoma Diagnosis with Contrastive Learning and LLM-based Report Generation
Junwen Zheng, Xinran Xu, Li Rong Wang +5
Deep learning has demonstrated expert-level performance in melanoma classification, positioning it as a powerful tool in clinical dermatology. However, model opacity and the lack o…
Towards Trustworthy Vital Sign Forecasting: Leveraging Uncertainty for Prediction Intervals
Li Rong Wang, Thomas C. Henderson, Yew Soon Ong +2
Vital signs, such as heart rate and blood pressure, are critical indicators of patient health and are widely used in clinical monitoring and decision-making. While deep learning mo…
Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
Woon Yee Ng, Li Rong Wang, Siyuan Liu +1
Explaining machine learning (ML) predictions has become crucial as ML models are increasingly deployed in high-stakes domains such as healthcare. While SHapley Additive exPlanation…