53 citations · 83 across the 7 of their papers we have counts for
8 papers
Layer Adaptive Deep Neural Networks for Out-of-distribution Detection
Haoliang Wang, Chen Zhao, Xujiang Zhao +1
During the forward pass of Deep Neural Networks (DNNs), inputs gradually transformed from low-level features to high-level conceptual labels. While features at different layers cou…
SEED: Sound Event Early Detection via Evidential Uncertainty
Xujiang Zhao, Xuchao Zhang, Wei Cheng +4
Sound Event Early Detection (SEED) is an essential task in recognizing the acoustic environments and soundscapes. However, most of the existing methods focus on the offline sound e…
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation
Liyan Xu, Xuchao Zhang, Xujiang Zhao +3
Recent multilingual pre-trained language models have achieved remarkable zero-shot performance, where the model is only finetuned on one source language and directly evaluated on t…
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
Krishnateja Killamsetty, Xujiang Zhao, Feng Chen +1
Semi-supervised learning (SSL) algorithms have had great success in recent years in limited labeled data regimes. However, the current state-of-the-art SSL algorithms are computati…
Multidimensional Uncertainty-Aware Evidential Neural Networks
Yibo Hu, Yuzhe Ou, Xujiang Zhao +2
Traditional deep neural networks (NNs) have significantly contributed to the state-of-the-art performance in the task of classification under various application domains. However,…
Uncertainty Aware Semi-Supervised Learning on Graph Data
Xujiang Zhao, Feng Chen, Shu Hu +1
Thanks to graph neural networks (GNNs), semi-supervised node classification has shown the state-of-the-art performance in graph data. However, GNNs have not considered different ty…