5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood
Gilhyun Nam, Taewon Kim, Joonhyun Jeong +1
Test-time adaptation (TTA) enables efficient adaptation of deployed models, yet it often leads to poorly calibrated predictive uncertainty - a critical issue in high-stakes domains…
cs.CV2023★ 5 cited
PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization
Junhyeong Cho, Gilhyun Nam, Sungyeon Kim +2
In a joint vision-language space, a text feature (e.g., from "a photo of a dog") could effectively represent its relevant image features (e.g., from dog photos). Also, a recent stu…
cs.CV2022
GCISG: Guided Causal Invariant Learning for Improved Syn-to-real Generalization
Gilhyun Nam, Gyeongjae Choi, Kyungmin Lee
Training a deep learning model with artificially generated data can be an alternative when training data are scarce, yet it suffers from poor generalization performance due to a la…