Noise Contrastive Test-Time Training: Enhancing Model Robustness through Unsupervised Adaptation

Noise Contrastive Test-Time Training (NC-TTT) is an innovative approach that leverages noise contrastive estimation to enable unsupervised adaptation of deep learning models at test time, improving their robustness to domain shifts.