Poster "out-of-distribution detection" Papers
29 papers found
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification
Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar et al.
Detecting Out-of-Distribution Through the Lens of Neural Collapse
Litian Liu, Yao Qin
DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection
Francisco Caetano, Christiaan Viviers, Luis Zavala-Mondragón et al.
Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
Shenzhi Yang, Junbo Zhao, Sharon Li et al.
MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian et al.
Mysteries of the Deep: Role of Intermediate Representations in Out of Distribution Detection
Ignacio Meza De la Jara, Cristian Rodriguez-Opazo, Damien Teney et al.
Noisy Test-Time Adaptation in Vision-Language Models
Chentao Cao, Zhun Zhong, (Andrew) Zhanke Zhou et al.
OOD-Barrier: Build a Middle-Barrier for Open-Set Single-Image Test Time Adaptation via Vision Language Models
Boyang Peng, Sanqing Qu, Tianpei Zou et al.
Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection
Hengzhuang Li, Teng Zhang
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Yingwen Wu, Ruiji Yu, Xinwen Cheng et al.
Refining Norms: A Post-hoc Framework for OOD Detection in Graph Neural Networks
Jiawei Gu, Ziyue Qiao, Zechao Li
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Jihyo Kim, Seulbi Lee, Sangheum Hwang
Towards Generalizable Detector for Generated Image
Qianshu Cai, Chao Wu, Yonggang Zhang et al.
Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation
Gianni Franchi, Nacim Belkhir, Dat NGUYEN et al.
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
A Geometric Explanation of the Likelihood OOD Detection Paradox
Hamidreza Kamkari, Brendan Ross, Jesse Cresswell et al.
A Provable Decision Rule for Out-of-Distribution Detection
Xinsong Ma, Xin Zou, Weiwei Liu
A Rate-Distortion View of Uncertainty Quantification
Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen et al.
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
Shenzhi Yang, Bin Liang, An Liu et al.
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
Chentao Cao, Zhun Zhong, Zhanke Zhou et al.
Fast Decision Boundary based Out-of-Distribution Detector
Litian Liu, Yao Qin
GalLop: Learning global and local prompts for vision-language models
Marc Lafon, Elias Ramzi, Clément Rambour et al.
Measuring Stochastic Data Complexity with Boltzmann Influence Functions
Nathan Ng, Roger Grosse, Marzyeh Ghassemi
Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
Chenhui Xu, Fuxun Yu, Zirui Xu et al.
SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning
ZERUN WANG, Liuyu Xiang, Lang Huang et al.
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
Anthony Chen, Huanrui Yang, Yulu Gan et al.
Uncertainty Estimation by Density Aware Evidential Deep Learning
Taeseong Yoon, Heeyoung Kim
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li