Ignavier Ng

403 citations
4 papers · 27 · h-index 3

Impact in

Papers in

Journals
arXiv (Cornell University) (1 paper)International Journal of Geographical Information Systems (1 paper)Neural Information Processing Systems (1 paper)
Partner nations
ChinaUnited States

In The Last Decade

Ignavier Ng

3 papers receiving 27 citations

Peers

Ignavier Ng
Comparison fields: 5 of 24
  • Transportation 6
  • Geography, Planning and Development 3
  • Modeling and Simulation 2
  • Process Chemistry and Technology 1
  • Artificial Intelligence 11
Replace Yunfan Gao with:
Yunfan Gao China
Riham Mansour Egypt
Maya John Saudi Arabia
L. F. Chaparro Sierra Colombia
Rahib Imamguluyev Azerbaijan
H. Y. Zhang China
Theo Damoulas United Kingdom
Junyuan Xie China
Eliza Szczechla Poland
R. Bhaskaran India
Ignavier Ng relative to Yunfan Gao China Yunfan Gao's profile →
Citations per field
00.5×1.6×
Yunfan Gao · 1×
Citations per year

Countries citing papers authored by Ignavier Ng

Since Specialization
Citations

This map shows the geographic impact of Ignavier Ng'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 Ignavier Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ignavier Ng more than expected).

Fields of papers citing papers by Ignavier Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ignavier Ng. 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 Ignavier Ng. The network helps show where Ignavier Ng may publish in the future.

Co-authors

The 10 scholars most cited alongside Ignavier Ng, 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 Ignavier Ng Line = papers co-authored together Ignavier Ng links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1 202215
2
Causal Discovery with Reinforcement Learning
20209
3
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
20203
4 20220

About Ignavier Ng

Ignavier Ng is a scholar working on Artificial Intelligence, Signal Processing, Epidemiology, Computational Theory and Mathematics and Transportation, having authored 4 papers that have together received 27 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (2 papers), Bayesian Modeling and Causal Inference (2 papers), Blind Source Separation Techniques (1 paper), Computational Drug Discovery Methods (1 paper), Machine Learning and Algorithms (1 paper), Data-Driven Disease Surveillance (1 paper), Spatial and Panel Data Analysis (1 paper) and Human Mobility and Location-Based Analysis (1 paper). The work is most often cited by research in Transportation (6 citations), Geography, Planning and Development (3 citations), Modeling and Simulation (2 citations), Process Chemistry and Technology (1 citation) and Artificial Intelligence (11 citations). Ignavier Ng has collaborated with scholars based in China and United States. Frequent co-authors include Shengyu Zhu, Zhitang Chen, Teng Fei, Fan Zhang, Yuhao Kang, Song Gao, Shan Ye, Jinmeng Rao, Kun Zhang and Yujia Zheng. Their work appears in journals such as arXiv (Cornell University), International Journal of Geographical Information Systems and Neural Information Processing Systems.

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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