共 50 条
- [1] SELF-TRAINING OF GRAPH NEURAL NETWORKS USING SIMILARITY REFERENCE FOR ROBUST TRAINING WITH NOISY LABELS [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2020, : 1951 - 1955
- [2] Robust Training of Deep Neural Networks with Noisy Labels by Graph Label Propagation [J]. FRONTIERS OF COMPUTER VISION, IW-FCV 2021, 2021, 1405 : 281 - 293
- [3] Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels [J]. PROCEEDINGS OF THE 17TH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING, WSDM 2024, 2024, : 712 - 720
- [5] Self-supervised robust Graph Neural Networks against noisy graphs and noisy labels [J]. Applied Intelligence, 2023, 53 : 25154 - 25170
- [7] Training Robust Deep Neural Networks on Noisy Labels Using Adaptive Sample Selection With Disagreement [J]. IEEE ACCESS, 2021, 9 : 141131 - 141143
- [9] Improving Graph Neural Networks by combining active learning with self-training [J]. Data Mining and Knowledge Discovery, 2024, 38 : 110 - 127
- [10] Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 2018, 31