Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer: From First Principles to Tensor Valued Back-Propagation

14 March 2019

Papers citing "Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer: From First Principles to Tensor Valued Back-Propagation"

4 / 4 papers shown

Title
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement Gaurav Patel Christopher Sandino Behrooz Mahasseni Ellen L. Zippi Erdrin Azemi Ali Moin Juri Minxha TTA AI4TS 55 3 0 03 Oct 2024
Spatial-temporal traffic modeling with a fusion graph reconstructed by tensor decomposition Qin Li Xu Yang Yong Wang Yuankai Wu Deqiang He 44 10 0 12 Dec 2022
Tensor decomposition to Compress Convolutional Layers in Deep Learning Yinan Wang W. Guo Xiaowei Yue 6 15 0 28 May 2020
Bayesian Tensorized Neural Networks with Automatic Rank Selection Cole Hawkins Zheng-Wei Zhang BDL 25 52 0 24 May 2019