This map shows the geographic impact of Vikas Garg'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 Vikas Garg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vikas Garg more than expected).
This network shows the impact of papers produced by Vikas Garg. 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 Vikas Garg. The network helps show where Vikas Garg may publish in the future.
Co-authorship network of co-authors of Vikas Garg
This figure shows the co-authorship network connecting the top 25 collaborators of Vikas Garg.
A scholar is included among the top collaborators of Vikas Garg 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 Vikas Garg. Vikas Garg is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ingraham, John, Vikas Garg, Regina Barzilay, & Tommi Jaakkola. (2019). Generative models for graph-based protein design. DSpace@MIT (Massachusetts Institute of Technology). 32. 15794–15805.98 indexed citations
8.
Garg, Vikas, et al.. (2019). Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms. Neural Information Processing Systems. 32. 5680–5690.1 indexed citations
9.
Singh, Gurinder, et al.. (2019). Information Security Parameters Used By Aadhar, Uidai And It’s Impact. International journal of scientific and technology research. 8(10). 1150–1154.
Garg, Vikas & Adam Tauman Kalai. (2018). Supervising Unsupervised Learning. Neural Information Processing Systems. 31. 4991–5001.2 indexed citations
12.
Garg, Vikas, et al.. (2018). A Study on Investment Preference towards Different Investment Avenues. Journal of Emerging Technologies and Innovative Research. 5(7). 1535-1539–1535-1539.
13.
Garg, Vikas & Tommi Jaakkola. (2017). Local Aggregative Games. Neural Information Processing Systems. 30. 5341–5351.1 indexed citations
14.
Garg, Vikas, et al.. (2016). Detecting malicious node in network using packet delivery ratio. International Conference on Computing for Sustainable Global Development. 3313–3318.2 indexed citations
15.
Garg, Vikas, Cynthia Rudin, & Tommi Jaakkola. (2016). CRAFT: ClusteR-specific Assorted Feature selecTion. DSpace@MIT (Massachusetts Institute of Technology). 305–313.2 indexed citations
16.
Garg, Vikas & Tommi Jaakkola. (2016). Learning Tree Structured Potential Games. DSpace@MIT (Massachusetts Institute of Technology). 29. 1552–1560.2 indexed citations
17.
Kondor, Risi, et al.. (2014). Multiresolution Matrix Factorization. International Conference on Machine Learning. 1620–1628.19 indexed citations
18.
Kpotufe, Samory & Vikas Garg. (2013). Adaptivity to Local Smoothness and Dimension in Kernel Regression. Max Planck Digital Library. 26. 3075–3083.12 indexed citations
19.
Garg, Vikas. (2012). Dimensions of Internal Auditing. 1(9).
20.
Garg, Vikas, et al.. (2009). Efficient Market Hypothesis: A Critical Review of Theory and Its Implications for Investment Decision. 3(2). 8–17.2 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.