175 citations · 478 across the 28 of their papers we have counts for
6 papers · 1 filter
Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning
Wenzhuo Liu, Xinjian Wu, Fei Zhu +3
Deep Neural Network (DNN) has achieved great success on datasets of closed class set. However, new classes, like new categories of social media topics, are continuously added to th…
OpenMix: Exploring Outlier Samples for Misclassification Detection
Fei Zhu, Zhen Cheng, Xu-Yao Zhang +1
Reliable confidence estimation for deep neural classifiers is a challenging yet fundamental requirement in high-stakes applications. Unfortunately, modern deep neural networks are…
Rethinking Confidence Calibration for Failure Prediction
Fei Zhu, Zhen Cheng, Xu-Yao Zhang +1
Reliable confidence estimation for the predictions is important in many safety-critical applications. However, modern deep neural networks are often overconfident for their incorre…
Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection
Zhen Cheng, Fei Zhu, Xu-Yao Zhang +1
Detecting Out-of-distribution (OOD) inputs have been a critical issue for neural networks in the open world. However, the unstable behavior of OOD detection along the optimization…
Dynamics-Aware Loss for Learning with Label Noise
Xiu-Chuan Li, Xiaobo Xia, Fei Zhu +3
Label noise poses a serious threat to deep neural networks (DNNs). Employing robust loss functions which reconcile fitting ability with robustness is a simple but effective strateg…
A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram
Ming-Liang Zhang, Fei Yin, Cheng-Lin Liu
Geometry problem solving (GPS) is a high-level mathematical reasoning requiring the capacities of multi-modal fusion and geometric knowledge application. Recently, neural solvers h…