Summary of Transformers For Supervised Online Continual Learning, by Jorg Bornschein et al.
Transformers for Supervised Online Continual Learningby Jorg Bornschein, Yazhe Li, Amal Rannen-TrikiFirst submitted to arxiv…
Transformers for Supervised Online Continual Learningby Jorg Bornschein, Yazhe Li, Amal Rannen-TrikiFirst submitted to arxiv…
Can a Confident Prior Replace a Cold Posterior?by Martin Marek, Brooks Paige, Pavel IzmailovFirst submitted…
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Modelby Huan Ma, Yan Zhu, Changqing…
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlationby Fahimeh Hosseini Noohdani, Parsa Hosseini, Aryan Yazdan…
Orchid: Flexible and Data-Dependent Convolution for Sequence Modelingby Mahdi Karami, Ali GhodsiFirst submitted to arxiv…
Deep Neural Network Models Trained With A Fixed Random Classifier Transfer Better Across Domainsby Hafiz…
Classes Are Not Equal: An Empirical Study on Image Recognition Fairnessby Jiequan Cui, Beier Zhu,…
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizersby Yiwei Lu, Yaoliang Yu, Xinlin…
Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculumby Hanbing Liu, Jingge Wang, Xuan Zhang, Ye…
Searching a Lightweight Network Architecture for Thermal Infrared Pedestrian Trackingby Wen-Jia Tang, Xiao Liu, Peng…