Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination

17 October 2020

Papers citing "Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination"

8 / 8 papers shown

Title
Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks Yequan Zhao Xinling Yu Xian Xiao Zhengzhang Chen Z. Liu G. Kurczveil R. Beausoleil Shixuan Liu Z. Zhang 56 0 0 17 Feb 2025
Structure-Preserving Network Compression Via Low-Rank Induced Training Through Linear Layers Composition Xitong Zhang Ismail R. Alkhouri Rongrong Wang 41 0 0 06 May 2024
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression Jiaqi Gu Ben Keller Jean Kossaifi Anima Anandkumar Brucek Khailany David Z. Pan ViT 35 8 0 30 Nov 2022
Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey Dalin Zhang Kaixuan Chen Yan Zhao B. Yang Li-Ping Yao Christian S. Jensen 48 3 0 22 Aug 2022
TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing Z. Liu Xinling Yu Zheng-Wei Zhang PINN 16 7 0 04 Jul 2022
3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration Yao Chen Cole Hawkins Kaiqi Zhang Zheng-Wei Zhang Cong Hao 26 8 0 11 May 2021
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 337 1,049 0 10 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016