Leyuan Wang

52 papers receiving 1.4k citations

Hit Papers

TVM: an automated end-to-end optimizing compiler for deep learning 2018 · 522 citations
5220+2+5Years since publication100200300400500

Peers

Leyuan Wang
Comparison fields: 5 of 134
  • Computational Mathematics 32
  • Hardware and Architecture 275
  • Computer Vision and Pattern Recognition 589
  • Artificial Intelligence 367
  • Cancer Research 143
Replace Dongyoung Kim with:
Dongyoung Kim South Korea
Jongeun Lee South Korea
Georgios Goumas Greece
Peipei Zhou United States
Nectarios Koziris Greece
Alioune Ngom Canada
Yuedan Chen China
Yadong Wang China
Minsu Cho South Korea
Matthew Walker United States
Leyuan Wang relative to Dongyoung Kim South Korea Dongyoung Kim's profile →
Citations per field
00.5×3.1×
Dongyoung Kim · 1×
Citations per year

Countries citing papers authored by Leyuan Wang

Since Specialization
Citations

This map shows the geographic impact of Leyuan Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Leyuan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leyuan Wang more than expected).

Fields of papers citing papers by Leyuan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leyuan Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Leyuan Wang. The network helps show where Leyuan Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Leyuan Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Leyuan Wang Line = papers co-authored together Leyuan Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1
TVM: an automated end-to-end optimizing compiler for deep learning
Hit paper breakdown →
2018522
2 2015110
3 2018100
4 201786
5 201560
6 201959
7 201937
8 201932
9
HAWQ-V3: Dyadic Neural Network Quantization
202130
10 202327
11 201226
12 202023
13 202022
14 201821
15 201921
16 202018
17 202517
18 202017
19 202014
20 201813

About Leyuan Wang

Leyuan Wang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Immunology and Artificial Intelligence, having authored 55 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neonatal Respiratory Health Research (10 papers), Respiratory viral infections research (5 papers), Epigenetics and DNA Methylation (5 papers), Extracellular vesicles in disease (5 papers), Asthma and respiratory diseases (4 papers), Advanced Neural Network Applications (4 papers), Pediatric health and respiratory diseases (4 papers) and Cancer-related molecular mechanisms research (4 papers). The work is most often cited by research in Computational Mathematics (32 citations), Hardware and Architecture (275 citations), Computer Vision and Pattern Recognition (589 citations), Artificial Intelligence (367 citations) and Cancer Research (143 citations). Leyuan Wang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Lianmin Zheng, Arvind Krishnamurthy, Meghan Cowan, Luís Ceze, Haichen Shen, Yuwei Hu, Thierry Moreau, Tianqi Chen, Carlos Guestrin and Ziheng Jiang. Their work appears in journals such as Journal of Cellular and Molecular Medicine, Scientific Reports, Journal of Translational Medicine, Biomedicine & Pharmacotherapy and Frontiers in Oncology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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