1 code implementation • 16 Mar 2024 • Uiwon Hwang, Jonghyun Lee, Juhyeon Shin, Sungroh Yoon
We construct an augmentation graph in the feature space of the pretrained model using the neighbor relationships between target features and propose spectral neighborhood clustering to identify partitions in the prediction space.
no code implementations • 12 Mar 2024 • Jonghyun Lee, Dahuin Jung, Saehyung Lee, Junsung Park, Juhyeon Shin, Uiwon Hwang, Sungroh Yoon
To mitigate it, TTA methods have utilized the model output's entropy as a confidence metric that aims to determine which samples have a lower likelihood of causing error.
no code implementations • 14 Feb 2024 • Juhyeon Shin, Jonghyun Lee, Saehyung Lee, MinJun Park, Dongjun Lee, Uiwon Hwang, Sungroh Yoon
In context of Test-time Adaptation(TTA), we propose a regularizer, dubbed Gradient Alignment with Prototype feature (GAP), which alleviates the inappropriate guidance from entropy minimization loss from misclassified pseudo label.