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.
Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection
20191.0k citationsVuong Le, Svetha Venkatesh et al.profile →
Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
2016695 citationsWei Luo, Dinh Phung et al.profile →
GraphDTA: predicting drug–target binding affinity with graph neural networks
2020629 citationsThin Nguyen, Hang Le et al.Bioinformaticsprofile →
Countries citing papers authored by Svetha Venkatesh
Since
Specialization
Citations
This map shows the geographic impact of Svetha Venkatesh'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 Svetha Venkatesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Svetha Venkatesh more than expected).
Fields of papers citing papers by Svetha Venkatesh
This network shows the impact of papers produced by Svetha Venkatesh. 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 Svetha Venkatesh. The network helps show where Svetha Venkatesh may publish in the future.
Co-authorship network of co-authors of Svetha Venkatesh
This figure shows the co-authorship network connecting the top 25 collaborators of Svetha Venkatesh.
A scholar is included among the top collaborators of Svetha Venkatesh 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 Svetha Venkatesh. Svetha Venkatesh is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Nguyen, Thin, Hang Le, Thomas P. Quinn, et al.. (2020). GraphDTA: predicting drug–target binding affinity with graph neural networks. Bioinformatics. 37(8). 1140–1147.629 indexed citations breakdown →
Lê, Hung, Truyen Tran, & Svetha Venkatesh. (2019). Learning to Remember More with Less Memorization. Own your potential (DEAKIN).4 indexed citations
11.
Nguyen, Vu, Sunil Gupta, Santu Rana, Cheng Li, & Svetha Venkatesh. (2017). Regret for expected improvement over the best-observed value and stopping condition. Figshare. 279–294.19 indexed citations
12.
Vellanki, Pratibha, Santu Rana, Sunil Gupta, et al.. (2017). Process-constrained batch Bayesian optimisation. Deakin Research Online (Deakin University). 30. 3414–3423.5 indexed citations
13.
Shilton, Alistair, Sunil Gupta, Santu Rana, & Svetha Venkatesh. (2017). Regret bounds for transfer learning in Bayesian optimisation. Own your potential (DEAKIN). 307–315.5 indexed citations
14.
Nguyen, Vu, Sunil Gupta, Santu Rana, Cheng Li, & Svetha Venkatesh. (2016). A Bayesian Nonparametric Approach for Multi-label Classification. Own your potential (DEAKIN). 254–269.6 indexed citations
Gupta, Sunil, Dinh Phung, & Svetha Venkatesh. (2012). A nonparametric Bayesian Poisson Gamma model for count data. Deakin Research Online (Deakin University).8 indexed citations
17.
Phung, Dinh, et al.. (2008). Indoor location prediction using multiple wireless received signal strengths. Deakin Research Online (Deakin University). 187–192.7 indexed citations
18.
Liu, Wanquan, et al.. (2006). Automatic parameters selection for eigenfaces. Deakin Research Online (Deakin University). 2(2). 277–288.1 indexed citations
19.
Lazarescu, Mihai & Svetha Venkatesh. (2003). Using selective memory to track concept drift effectively. Deakin Research Online (Deakin University). 14–19.5 indexed citations
20.
Venkatesh, Svetha, et al.. (2002). Coordination of multiple cameras to track multiple people. Deakin Research Online (Deakin University). 302–307.2 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.