NHP: Neural Hypergraph Link Prediction-Reference-Cited by-同舟云学术

NHP: Neural Hypergraph Link Prediction

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Information & Knowledge Management
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Author:

Yadati Naganand¹,Nitin Vikram²,Nimishakavi Madhav³,Yadav Prateek⁴,Louis Anand¹,Talukdar Partha¹

Affiliation:

1. Indian Institute of Science, Bangalore, India

2. Columbia University, New York, NY, USA

3. Facebook AI, London, United Kingdom

4. LinkedIn, Bangalore, India

Funder

Ministry of Human Resource Development

SERB Award

Pratiksha Trust Young Investigator Award

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3340531.3411870

Reference44 articles.

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2. Haoli Bai Zhuangbin Chen Michael R. Lyu Irwin King and Zenglin Xu. 2018. Neural Relational Topic Models for Scientific Article Analysis. In CIKM. Haoli Bai Zhuangbin Chen Michael R. Lyu Irwin King and Zenglin Xu. 2018. Neural Relational Topic Models for Scientific Article Analysis. In CIKM.

3. Peter W. Battaglia Jessica B. Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vin'i cius Flores Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner cC aglar Gü lcc ehre Francis Song Andrew J. Ballard Justin Gilmer George E. Dahl Ashish Vaswani Kelsey Allen Charles Nash Victoria Langston Chris Dyer Nicolas Heess Daan Wierstra Pushmeet Kohli Matthew Botvinick Oriol Vinyals Yujia Li and Razvan Pascanu. 2018. Relational inductive biases deep learning and graph networks. CoRR arXiv:1806.01261 (2018). Peter W. Battaglia Jessica B. Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vin'i cius Flores Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner cC aglar Gü lcc ehre Francis Song Andrew J. Ballard Justin Gilmer George E. Dahl Ashish Vaswani Kelsey Allen Charles Nash Victoria Langston Chris Dyer Nicolas Heess Daan Wierstra Pushmeet Kohli Matthew Botvinick Oriol Vinyals Yujia Li and Razvan Pascanu. 2018. Relational inductive biases deep learning and graph networks. CoRR arXiv:1806.01261 (2018).

4. Michael M. Bronstein Joan Bruna Yann LeCun Arthur Szlam and Pierre Vandergheynst. 2017. Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. (2017). Michael M. Bronstein Joan Bruna Yann LeCun Arthur Szlam and Pierre Vandergheynst. 2017. Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. (2017).

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