87 citations · 719 across the 60 of their papers we have counts for
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cs.LG2022★ 1 cited
Dimensionality-Varying Diffusion Process
Han Zhang, Ruili Feng, Zhantao Yang +7
Diffusion models, which learn to reverse a signal destruction process to generate new data, typically require the signal at each step to have the same dimension. We argue that, con…
cs.LG2022
Neural Dependencies Emerging from Learning Massive Categories
Ruili Feng, Kecheng Zheng, Kai Zhu +7
This work presents two astonishing findings on neural networks learned for large-scale image classification. 1) Given a well-trained model, the logits predicted for some category c…
cs.LG2020★ 20 cited
Residual Knowledge Distillation
Mengya Gao, Yujun Shen, Quanquan Li +1
Knowledge distillation (KD) is one of the most potent ways for model compression. The key idea is to transfer the knowledge from a deep teacher model (T) to a shallower student (S)…