Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Stanley Kok'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 Stanley Kok with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stanley Kok more than expected).
This network shows the impact of papers produced by Stanley Kok. 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 Stanley Kok. The network helps show where Stanley Kok may publish in the future.
Co-authorship network of co-authors of Stanley Kok
This figure shows the co-authorship network connecting the top 25 collaborators of Stanley Kok.
A scholar is included among the top collaborators of Stanley Kok based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Stanley Kok. Stanley Kok is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kok, Stanley, et al.. (2020). Generating Privacy-Preserving Synthetic Tabular Data Using Oblivious Variational Autoencoders. National University of Singapore.8 indexed citations
7.
Kok, Stanley, et al.. (2020). Synthetic Tabular Data Generation with Oblivious Variational Autoencoders : Alleviating the Paucity of Personal Tabular Data for Open Research. National University of Singapore.3 indexed citations
Kok, Stanley, et al.. (2018). Unconstrained Product Categorization with Sequence-to-Sequence Models. National University of Singapore.2 indexed citations
10.
Tan, Liling, et al.. (2018). Unconstrained Production Categorization with Sequence-to-Sequence Models.. International ACM SIGIR Conference on Research and Development in Information Retrieval.1 indexed citations
Kok, Stanley & Pedro Domingos. (2010). Learning Markov Logic Networks Using Structural Motifs. International Conference on Machine Learning. 551–558.58 indexed citations
16.
Kok, Stanley & Chris Brockett. (2010). Hitting the Right Paraphrases in Good Time. North American Chapter of the Association for Computational Linguistics. 145–153.40 indexed citations
17.
Kok, Stanley & Pedro Domingos. (2010). Using structural motifs for learning Markov logic networks. National University of Singapore. 46–51.1 indexed citations
18.
Kok, Stanley & Wen-tau Yih. (2009). Extracting Product Information from Email Receipts Using Markov Logic. National University of Singapore.2 indexed citations
19.
Domingos, Pedro, Stanley Kok, Daniel Lowd, et al.. (2008). Markov logic. 92–117.42 indexed citations
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.