2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.AI2023
Empirical Optimal Risk to Quantify Model Trustworthiness for Failure Detection
Shuang Ao, Stefan Rueger, Advaith Siddharthan
Failure detection (FD) in AI systems is a crucial safeguard for the deployment for safety-critical tasks. The common evaluation method of FD performance is the Risk-coverage (RC) c…
cs.LG2023★ 2 cited
Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration
Shuang Ao, Stefan Rueger, Advaith Siddharthan
Proper confidence calibration of deep neural networks is essential for reliable predictions in safety-critical tasks. Miscalibration can lead to model over-confidence and/or under-…
cs.CV2023
Confidence-Aware Calibration and Scoring Functions for Curriculum Learning
Shuang Ao, Stefan Rueger, Advaith Siddharthan
Despite the great success of state-of-the-art deep neural networks, several studies have reported models to be over-confident in predictions, indicating miscalibration. Label Smoot…