Lihui Chen

Graph Learning · with Liu · 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; #591 of 693 by trust here, #392 by citations
• Artificial Intelligence — 12 citations into it; #30,092 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; #2,716 of 3,145 by trust here, #1,943 by citations
• Molecular Biology — 5 citations into it

Whom Lihui Chen trusts overall

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

1. Brendan J. Frey
2. Nino Shervashidze
3. Tomas Mikolov
4. Pinar Yanardag

Who trusts Lihui Chen overall

1. Aynaz Taheri
2. Evgeny Burnaev

Papers from Lihui Chen's perspective

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

1. Efficient Estimation of Word Representations in Vector Space
2. Shortest-path kernels on graphs
3. Graph Kernels
4. DeepWalk: online learning of social representations
5. Protein function prediction via graph kernels
6. Weisfeiler-Lehman Graph Kernels
7. Cyclic pattern kernels for predictive graph mining
8. node2vec: Scalable Feature Learning for Networks
9. Deep Graph Kernels
10. Fast Neighborhood Subgraph Pairwise Distance Kernel

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