王登豹，东南大学计算机科学与工程学院讲师，硕士生导师。2024年于东南大学计算机科学与工程学院获得博士学位，师从张敏灵教授。研究领域为人工智能、机器学习，目前主要关注大模型的不确定性估计问题。 在机器学习、数据挖掘、人工智能相关领域的顶级会议与权威期刊上（ICML、NeurIPS、KDD、AAAI、IEEE TPAMI 、IEEE TKDE 等）发表论文十余篇，获批首届 “NSFC 博士生基金” 项目，获德国学术交流中心 DAAD AInet Fellow 计划等奖励，并担任多个著名国际会议的程序委员以及期刊审稿人。更多信息请访问我的个人主页。
招收2026级硕士研究生，欢迎感兴趣的同学与我邮件联系！也欢迎本科生联系我参与科研训练！Let's do some fun research!
# 共同一作，完整论文列表见谷歌学术主页
[SSI'25] Investigating the Confidence Calibratability of Deep Neural Networks (in Chinese)
D.-B. Wang, M.-L. Zhang
SCIENTIA SINICA Informationis (中国科学：信息科学), in press. CCF-A
[ICML'24] Calibration Bottleneck: Over-compressed Representations are Less Calibratable
D.-B. Wang, M.-L. Zhang
In: Proceedings of the 41st International Conference on Machine Learning, 2024, 52156-52170. CCF-A
[AAAI’24] Distilling Reliable Knowledge for Instance-dependent Partial Label Learning
D.-D. Wu#, D.-B. Wang#, M.-L. Zhang
In: Proceedings of the 38th AAAI Conference on Artificial Intelligence, 2024, 15888-15896. CCF-A
[CVPR’23] On the Pitfall of Mixup for Uncertainty Calibration
D.-B. Wang, L. Li, P. Zhao, P.-A. Heng, M.-L. Zhang
In: Proceedings of the 34th IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023, 7609-7618. CCF-A
[TPAMI’22] Adaptive Graph Guided Disambiguation for Partial Label Learning
D.-B. Wang, L. Li, M.-L. Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, 44(12): 8796-8811. CCF-A
[ICML’22] Revisiting Consistency Regularization for Deep Partial Label Learning
D.-D. Wu#, D.-B. Wang#, M.-L. Zhang
In: Proceedings of the 39th International Conference on Machine Learning, 2022, 24212-24225. CCF-A
[NeurIPS’21] Rethinking Calibration of Deep Neural Networks: Don’t Be Afraid of Overconfidence
D.-B. Wang, L. Feng, M.-L. Zhang
In: Advances in Neural Information Processing Systems 34, 2021, 11809-11820. CCF-A
[IJCAI’21] Learning from Complementary Labels via Partial-Output Consistency Regularization
D.-B. Wang, L. Feng, M.-L. Zhang
In: Proceedings of the 30th International Joint Conference on Artificial Intelligence, 2021, 3075-3081. CCF-A
[AAAI’21] Learning from Noisy Labels with Complementary Loss Functions
D.-B. Wang, Y. Wen, L. Pan, M.-L. Zhang
In: Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021, 10111-10119. CCF-A
[KDD’19] Adaptive Graph Guided Disambiguation for Partial Label Learning
D.-B. Wang, L. Li, M.-L. Zhang
In: Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2019, 83-91. CCF-A
