13 citations · 50 across the 18 of their papers we have counts for
4 papers · 1 filter
IMBENS: Ensemble Class-imbalanced Learning in Python
Zhining Liu, Jian Kang, Hanghang Tong +1
imbalanced-ensemble, abbreviated as imbens, is an open-source Python toolbox for leveraging the power of ensemble learning to address the class imbalance problem. It provides stand…
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks
Haotian Xue, Kaixiong Zhou, Tianlong Chen +4
Despite the recent advances of graph neural networks (GNNs) in modeling graph data, the training of GNNs on large datasets is notoriously hard due to the overfitting. Adversarial t…
Orthogonal Graph Neural Networks
Kai Guo, Kaixiong Zhou, Xia Hu +3
Graph neural networks (GNNs) have received tremendous attention due to their superiority in learning node representations. These models rely on message passing and feature transfor…
The EIHW-GLAM Deep Attentive Multi-model Fusion System for Cough-based COVID-19 Recognition in the DiCOVA 2021 Challenge
Zhao Ren, Yi Chang, Björn W. Schuller
Aiming to automatically detect COVID-19 from cough sounds, we propose a deep attentive multi-model fusion system evaluated on the Track-1 dataset of the DiCOVA 2021 challenge. Thre…