2025 Poster "distribution shift" Papers
10 papers found
AdaWM: Adaptive World Model based Planning for Autonomous Driving
Hang Wang, Xin Ye, Feng Tao et al.
ICLR 2025posterarXiv:2501.13072
13
citations
ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
Xincheng Yao, Yan Luo, Zefeng Qian et al.
NeurIPS 2025posterarXiv:2511.05245
1
citations
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
Xiran Wang, Jian Zhang, Lei Qi et al.
CVPR 2025posterarXiv:2503.18987
3
citations
Keep It on a Leash: Controllable Pseudo-label Generation Towards Realistic Long-Tailed Semi-Supervised Learning
Yaxin Hou, Bo Han, Yuheng Jia et al.
NeurIPS 2025posterarXiv:2510.03993
Knowledge Distillation of Uncertainty using Deep Latent Factor Model
Sehyun Park, Jongjin Lee, Yunseop Shin et al.
NeurIPS 2025posterarXiv:2510.19290
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
Gautam Chandrasekaran, Adam Klivans, Lin Lin Lee et al.
ICLR 2025posterarXiv:2502.16021
1
citations
MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian et al.
ICLR 2025posterarXiv:2410.03074
16
citations
Noisy Test-Time Adaptation in Vision-Language Models
Chentao Cao, Zhun Zhong, (Andrew) Zhanke Zhou et al.
ICLR 2025posterarXiv:2502.14604
4
citations
Optimizing importance weighting in the presence of sub-population shifts
Floris Holstege, Bram Wouters, Noud Giersbergen et al.
ICLR 2025posterarXiv:2410.14315
1
citations
Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
Byungjai Kim, Chanho Ahn, Wissam Baddar et al.
ICLR 2025poster
3
citations