Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation

11 November 2020

Papers citing "Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation"

26 / 26 papers shown

Title
Towards Understanding Knowledge Distillation Mary Phuong Christoph H. Lampert 42 314 0 27 May 2021
EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events Stefanos Antaris Dimitrios Rafailidis Sarunas Girdzijauskas 21 5 0 11 Nov 2020
Graph Representation Learning via Multi-task Knowledge Distillation Jiaqi Ma Qiaozhu Mei 34 18 0 11 Nov 2019
Contrastive Representation Distillation Yonglong Tian Dilip Krishnan Phillip Isola 65 1,037 0 23 Oct 2019
Dynamic Joint Variational Graph Autoencoders Sedigheh Mahdavi Shima Khoshraftar Aijun An BDL 22 24 0 04 Oct 2019
Variational Graph Recurrent Neural Networks Ehsan Hajiramezanali Arman Hasanzadeh N. Duffield Krishna R. Narayanan Mingyuan Zhou Xiaoning Qian BDL GNN 34 184 0 26 Aug 2019
Semi-Implicit Graph Variational Auto-Encoders Arman Hasanzadeh Ehsan Hajiramezanali N. Duffield Krishna R. Narayanan Mingyuan Zhou Xiaoning Qian BDL GNN 41 129 0 19 Aug 2019
Zero-shot Knowledge Transfer via Adversarial Belief Matching P. Micaelli Amos Storkey 19 228 0 23 May 2019
Data-Free Learning of Student Networks Hanting Chen Yunhe Wang Chang Xu Zhaohui Yang Chuanjian Liu Boxin Shi Chunjing Xu Chao Xu Qi Tian FedML 22 367 0 02 Apr 2019
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs A. Pareja Giacomo Domeniconi Jie Chen Tengfei Ma Toyotaro Suzumura H. Kanezashi Tim Kaler Tao B. Schardl Charles E. Leisersen GNN 67 1,051 0 26 Feb 2019
Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System Jiaxi Tang Ke Wang 32 186 0 19 Sep 2018
dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning Palash Goyal Sujit Rokka Chhetri A. Canedo 41 399 0 07 Sep 2018
Large scale distributed neural network training through online distillation Rohan Anil Gabriel Pereyra Alexandre Passos Róbert Ormándi George E. Dahl Geoffrey E. Hinton FedML 307 405 0 09 Apr 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 192 19,902 0 30 Oct 2017
Representation Learning on Graphs: Methods and Applications William L. Hamilton Rex Ying J. Leskovec GNN 65 1,970 0 17 Sep 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 178 129,831 0 12 Jun 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 253 15,066 0 07 Jun 2017
Convolutional Sequence to Sequence Learning Jonas Gehring Michael Auli David Grangier Denis Yarats Yann N. Dauphin AIMat 109 3,279 0 08 May 2017
DeepGraph: Graph Structure Predicts Network Growth Cheng Li Xiaoxiao Guo Qiaozhu Mei GNN 39 17 0 20 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 282 28,795 0 09 Sep 2016
node2vec: Scalable Feature Learning for Networks Aditya Grover J. Leskovec 101 10,800 0 03 Jul 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 59 19,448 0 09 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 104 149,474 0 22 Dec 2014
Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization Linhong Zhu Dong Guo Junming Yin Greg Ver Steeg Aram Galstyan 70 199 0 13 Nov 2014
DeepWalk: Online Learning of Social Representations Bryan Perozzi Rami Al-Rfou Steven Skiena HAI 166 9,735 0 26 Mar 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 108 2,114 0 21 Dec 2013