"out-of-distribution detection" Papers
37 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.
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.
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
Prior2Former - Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation
Sebastian Schmidt, Julius Koerner, Dominik Fuchsgruber et al.
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.
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
Xuanlong Yu, Gianni Franchi, Jindong Gu et al.
EAT: Towards Long-Tailed Out-of-Distribution Detection
Tong Wei, Bo-Lin Wang, Min-Ling Zhang
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.
How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection?
Soumya Suvra Ghosal, Yiyou Sun, Yixuan Li
Learning by Erasing: Conditional Entropy Based Transferable Out-of-Distribution Detection
Meng Xing, Zhiyong Feng, Yong Su et al.
Measuring Stochastic Data Complexity with Boltzmann Influence Functions
Nathan Ng, Roger Grosse, Marzyeh Ghassemi
Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning
Wenjun Miao, Guansong Pang, Xiao Bai et al.
Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
Chenhui Xu, Fuxun Yu, Zirui Xu et al.
Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
Jian Liang, Sheng, Zhengbo Wang 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.
TagFog: Textual Anchor Guidance and Fake Outlier Generation for Visual Out-of-Distribution Detection
Jiankang Chen, Tong Zhang, Wei-shi Zheng et al.
Uncertainty Estimation by Density Aware Evidential Deep Learning
Taeseong Yoon, Heeyoung Kim
Unsupervised Layer-Wise Score Aggregation for Textual OOD Detection
Maxime Darrin, Guillaume Staerman, Eduardo Dadalto Camara Gomes et al.
Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt Tuning
Kun Ding, Haojian Zhang, Qiang Yu et al.
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li