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Yixuan Li
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Stacked Generative Adversarial Networks
X Huang, Y Li, O Poursaeed, J Hopcroft, S Belongie
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
3946*2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
S Liang, Y Li, R Srikant
International Conference on Learning Representation (ICLR'18), 2018
21012018
Exploring the limits of weakly supervised pretraining
D Mahajan, R Girshick, V Ramanathan, K He, M Paluri, Y Li, A Bharambe, ...
Proceedings of the European conference on computer vision (ECCV), 181-196, 2018
15352018
Energy-based Out-of-distribution Detection
W Liu, X Wang, J Owens, Y Li
Advances in Neural Information Processing Systems 33, 2020
10662020
Snapshot Ensembles: Train 1, Get M for Free
G Huang*, Y Li*, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger
International Conference on Learning Representation (ICLR 2017), 2017
10432017
Generalized out-of-distribution detection: A survey
J Yang, K Zhou, Y Li, Z Liu
arXiv preprint arXiv:2110.11334, 2021
6742021
ReAct: Out-of-distribution Detection With Rectified Activations
Y Sun, C Guo, Y Li
Advances in Neural Information Processing Systems 34, 144-157, 2021
3512021
Convergent Learning: Do different neural networks learn the same representations?
Y Li, J Yosinski, J Clune, H Lipson, J Hopcroft
International Conference on Learning Representation (ICLR), 2016
3442016
Out-of-Distribution Detection with Deep Nearest Neighbors
Y Sun, Y Ming, X Zhu, Y Li
In Proceedings of International Conference on Machine Learning (ICML), 2022
3342022
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
R Huang, A Geng, Y Li
Advances in Neural Information Processing Systems (NeurIPS), 2021
2662021
VOS: Learning What You Don't Know by Virtual Outlier Synthesis
X Du, Z Wang, M Cai, Y Li
Proceedings of the International Conference on Learning Representations 1 (4), 8, 2022
2272022
Mitigating Neural Network Overconfidence with Logit Normalization
H Wei, R Xie, H Cheng, L Feng, B An, Y Li
In Proceedings of International Conference on Machine Learning (ICML), 2022
1932022
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
R Huang, Y Li
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
1922021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges
M Salehi, H Mirzaei, D Hendrycks, Y Li, MH Rohban, M Sabokrou
Transactions on Machine Learning Research (TMLR), 2022
1762022
Uncovering the small community structure in large networks: A local spectral approach
Y Li, K He, D Bindel, JE Hopcroft
Proceedings of the 24th international conference on world wide web, 658-668, 2015
1522015
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
J Yang, P Wang, D Zou, Z Zhou, K Ding, W Peng, H Wang, G Chen, B Li, ...
NeurIPS Datasets and Benchmarks Track, 2022
1502022
PiCO: Contrastive Label Disambiguation for Partial Label Learning
H Wang, R Xiao, S Li, L Feng, G Niu, G Chen, J Zhao
International Conference on Learning Representations (ICLR), 2022
1292022
DICE: Leveraging Sparsification for Out-of-Distribution Detection
Y Sun, Y Li
In Proceedings of European Conference on Computer Vision (ECCV), 691-708, 2022
1272022
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
J Chen, Y Li, X Wu, Y Liang, S Jha
Proceedings of European Conference on Machine Learning and Principles and …, 2021
1232021
Can multi-label classification networks know what they don't know?
H Wang, W Liu, A Bocchieri, Y Li
Advances in Neural Information Processing Systems (NeurIPS), 2021
1192021
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Artikelen 1–20