Annamalai Narayanan

Graph Learning · 2016–2017

A researcher in the Science corpus: 3 papers; trusts 16 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Graph Learning — 18 citations into it; #590 of 693 by trust here, #392 by citations
• Artificial Intelligence — 12 citations into it; #30,091 of 35,345 by trust here, #15,866 by citations
• Signal Processing — 9 citations into it
• Software — 9 citations into it
• Computer Networks and Communications — 8 citations into it
• Representation & Self-Supervised Learning — 8 citations into it; #2,715 of 3,145 by trust here, #1,943 by citations
• Molecular Biology — 5 citations into it

Whom Annamalai Narayanan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Nino Shervashidze
2. Brendan J. Frey
3. Tomas Mikolov
4. Pinar Yanardag
5. Aditya Grover
6. S. V. N. Vishwanathan
7. Karsten M. Borgwardt
8. Daniel Arp
9. Pinar Yanardag
10. Mathias Niepert

Who trusts Annamalai Narayanan overall

1. Aynaz Taheri
2. Yunsheng Bai
3. Kaveh Hassani
4. Zhang Xinyi
5. Sergey Ivanov
6. Yuning You
7. Fan-Yun Sun
8. Mahmood Yousefi-Azar
9. Jun Xia
10. Nikita Klyuchnikov

Papers from Annamalai Narayanan's perspective

Ordered by how strongly the researchers Annamalai Narayanan trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Efficient Estimation of Word Representations in Vector Space
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs (2016) — 160 citations
• graph2vec: Learning Distributed Representations of Graphs (2017) — 879 citations
• Contextual Weisfeiler-Lehman graph kernel for malware detection (2016) — 27 citations