Seguir
Sharon Li
Sharon Li
Otros nombresYixuan Li
University of Wisconsin-Madison
Dirección de correo verificada de cs.wisc.edu - Página principal
Título
Citado por
Citado por
Año
Stacked Generative Adversarial Networks
X Huang, Y Li, O Poursaeed, J Hopcroft, S Belongie
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
4393*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
25842018
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
17182018
Energy-based Out-of-distribution Detection
W Liu, X Wang, J Owens, Y Li
Advances in Neural Information Processing Systems 33, 2020
15652020
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
11902017
Generalized out-of-distribution detection: A survey
J Yang, K Zhou, Y Li, Z Liu
International Journal of Computer Vision 132 (12), 5635-5662, 2024
10982024
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
5842022
ReAct: Out-of-distribution Detection With Rectified Activations
Y Sun, C Guo, Y Li
Advances in Neural Information Processing Systems 34, 144-157, 2021
5362021
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
4072021
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
4042016
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
3632022
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
3302022
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
2882022
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
2832021
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
2632022
DICE: Leveraging Sparsification for Out-of-Distribution Detection
Y Sun, Y Li
In Proceedings of European Conference on Computer Vision (ECCV), 691-708, 2022
2132022
How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?
Y Ming, Y Sun, O Dia, Y Li
In Proceedings of the 11th International Conference on Learning …, 2023
1852023
Delving into Out-of-Distribution Detection with Vision-Language Representations
Y Ming, Z Cai, J Gu, Y Sun, W Li, Y Li
Advances in Neural Information Processing Systems (NeurIPS), 2022
1812022
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
1792021
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
1652021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20