Graph-based Knowledge Distillation: A survey and experimental evaluation

27 February 2023

Papers citing "Graph-based Knowledge Distillation: A survey and experimental evaluation"

9 / 9 papers shown

Title
Simple Graph Condensation Zhenbang Xiao Yu Wang Shunyu Liu Huiqiong Wang Mingli Song Tongya Zheng DD 61 6 0 22 Mar 2024
Training Self-localization Models for Unseen Unfamiliar Places via Teacher-to-Student Data-Free Knowledge Transfer Kenta Tsukahara Kanji Tanaka Daiki Iwata 21 2 0 13 Mar 2024
Data-centric Graph Learning: A Survey Jixi Liu Deyu Bo Cheng Yang Haoran Dai Qi Zhang Yixin Xiao Yufei Peng Chuan Shi GNN 16 19 0 08 Oct 2023
Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekstrom Kelvinius D. Georgiev Artur P. Toshev Johannes Gasteiger 11 6 0 26 Jun 2023
Iterative Graph Self-Distillation Hanlin Zhang Shuai Lin Weiyang Liu Pan Zhou Jian Tang Xiaodan Liang Eric P. Xing SSL 42 33 0 23 Oct 2020
Distilling Knowledge from Graph Convolutional Networks Yiding Yang Jiayan Qiu Mingli Song Dacheng Tao Xinchao Wang 141 222 0 23 Mar 2020
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud Weijing Shi Ragunathan R. Rajkumar 3DPC 139 731 0 02 Mar 2020
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Minjie Wang Da Zheng Zihao Ye Quan Gan Mufei Li ... J. Zhao Haotong Zhang Alex Smola Jinyang Li Zheng-Wei Zhang AI4CE GNN 182 731 0 03 Sep 2019
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 255 1,394 0 01 Dec 2016