39 citations · 54 across the 20 of their papers we have counts for
3 papers · 1 filter
Discovering Galaxy Features via Dataset Distillation
Haowen Guan, Xuan Zhao, Zishi Wang +2
In many applications, Neural Nets (NNs) have classification performance on par or even exceeding human capacity. Moreover, it is likely that NNs leverage underlying features that m…
Embarassingly Simple Dataset Distillation
Yunzhen Feng, Ramakrishna Vedantam, Julia Kempe
Dataset distillation extracts a small set of synthetic training samples from a large dataset with the goal of achieving competitive performance on test data when trained on this sa…
On the Robustness of Neural Collapse and the Neural Collapse of Robustness
Jingtong Su, Ya Shi Zhang, Nikolaos Tsilivis +1
Neural Collapse refers to the curious phenomenon in the end of training of a neural network, where feature vectors and classification weights converge to a very simple geometrical…