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…
CUPID: A Plug-in Framework for Joint Aleatoric and Epistemic Uncertainty Estimation with a Single Model
Xinran Xu, Xiuyi Fan
Accurate estimation of uncertainty in deep learning is critical for deploying models in high-stakes domains such as medical diagnosis and autonomous decision-making, where overconf…
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…
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…