8 citations · 11 across the 5 of their papers we have counts for
5 papers
Advancing Weight and Channel Sparsification with Enhanced Saliency
Xinglong Sun, Maying Shen, Hongxu Yin +3
Pruning aims to accelerate and compress models by removing redundant parameters, identified by specifically designed importance scores which are usually imperfect. This removal is…
Step Out and Seek Around: On Warm-Start Training with Incremental Data
Maying Shen, Hongxu Yin, Pavlo Molchanov +2
Data often arrives in sequence over time in real-world deep learning applications such as autonomous driving. When new training data is available, training the model from scratch u…
Fully Attentional Networks with Self-emerging Token Labeling
Bingyin Zhao, Zhiding Yu, Shiyi Lan +4
Recent studies indicate that Vision Transformers (ViTs) are robust against out-of-distribution scenarios. In particular, the Fully Attentional Network (FAN) - a family of ViT backb…
GHz sample excitation at the ALBA-PEEM
Muhammad Waqas Khaliq, José M. Álvarez, Antonio Camps +9
We describe a setup that is used for high-frequency electrical sample excitation in a cathode lens electron microscope with the sample stage at high voltage as used in many synchro…
VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion
Yiming Li, Zhiding Yu, Christopher Choy +5
Humans can easily imagine the complete 3D geometry of occluded objects and scenes. This appealing ability is vital for recognition and understanding. To enable such capability in A…