OOD (3) 썸네일형 리스트형 [논문리뷰]An Effective Baseline for Robustness to Distributional Shift 논문 링크 : https://arxiv.org/abs/2105.07107 An Effective Baseline for Robustness to Distributional Shift Refraining from confidently predicting when faced with categories of inputs different from those seen during training is an important requirement for the safe deployment of deep learning systems. While simple to state, this has been a particularly challeng arxiv.org 해당 논문은 OOD detection 방법 중 사전의.. [Survey] OOD(out-of-distribution) Detection 개념 분류 최근 OOD detection을 연구하면서, 해당 task와 유사한 다양한 task와 혼동되는 정의 및 활용을 명확히 정리하기 글을 쓰게 되었다. 아래의 링크는 정리를 위해 참고한 survey 논문이다. https://arxiv.org/abs/2110.11334 Generalized Out-of-Distribution Detection: A Survey Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of machine learning systems. For instance, in autonomous driving, we would like the driving system to issue an a.. [논문리뷰] Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty 논문 링크 :https://arxiv.org/abs/1906.12340https://ojs.aaai.org/index.php/AAAI/article/view/5966 Self-Supervised Learning for Generalizable Out-of-Distribution Detection | Proceedings of the AAAI Conference on Artifici ojs.aaai.org 최근 OOD(out-of-distribution) detection에 관심이 생겨서 이와 관련된 다양한 논문을 survey 중에 해당 논문을 발견했다. 해당 논문은 NIPS 2019 논문으로 Self-supervised learning을 accuracy관점이 아닌 모델의 Robustness 관점에서 바라.. 이전 1 다음
