Sriram Srinivasan

3.0k citations
72 papers · 1.4k indexed · 1 hit paper · h-index 17
Topics
Speech and Audio Processing (25 papers)Advanced Adaptive Filtering Techniques (18 papers)Complex Network Analysis Techniques (12 papers)

In The Last Decade

Sriram Srinivasan

66 papers receiving 1.3k citations

Hit Papers

Unifying count-based exploration and intrinsic motivation2016202620192022201650100150200250

Peers

Sriram Srinivasan
Comparison fields: 5 of 106
  • Artificial Intelligence 633
  • Signal Processing 507
  • Computational Mechanics 307
  • Electrical and Electronic Engineering 165
  • Computer Vision and Pattern Recognition 149
Replace F.M.A. Salam with:
F.M.A. Salam United States
David S. Pallett United States
Bin-Da Liu Taiwan
Christopher Morris United States
Shao‐Lun Huang China
Pedro J. Moreno United States
Dat Tran Australia
Xiaomei Yu China
Binghui Wang United States
P.W. Grant United Kingdom
Sriram Srinivasan relative to F.M.A. Salam United States F.M.A. Salam's profile →
Citations per field
00.5×9.2×
F.M.A. Salam · 1×
Citations per year

Countries citing papers authored by Sriram Srinivasan

Since Specialization
Citations

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

Fields of papers citing papers by Sriram Srinivasan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sriram Srinivasan

This figure shows the co-authorship network connecting the top 25 collaborators of Sriram Srinivasan. A scholar is included among the top collaborators of Sriram Srinivasan 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 Sriram Srinivasan. Sriram Srinivasan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 0
4 3
5 0
6 2
7 2
8 18
9 67
10 4
11 29
12
Unifying count-based exploration and intrinsic motivationbreakdown →
280
13 28
14 1
15 1
16 1
17 5
18
Robust spectrum quantization for LP parameter enhancement
4
19 14
20 13

About Sriram Srinivasan

Sriram Srinivasan is a scholar working on Signal Processing, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 72 papers that have together received 1.4k indexed citations. Recurring topics across this work include Speech and Audio Processing (25 papers), Advanced Adaptive Filtering Techniques (18 papers) and Complex Network Analysis Techniques (12 papers). The work is most often cited by research in Signal Processing (507 citations), Artificial Intelligence (633 citations) and Computational Mechanics (307 citations). Sriram Srinivasan has collaborated with scholars based in United States, India and Netherlands. Frequent co-authors include W. Bastiaan Kleijn, J. Samuelsson, Tom Schaul, David Saxton, Georg Ostrovski, Marc G. Bellemare, Rémi Munos, Yong Guo, Sheetal Gaiki and Sanjukta Bhowmick. Their work appears in journals such as Scientific Reports, The Journal of the Acoustical Society of America and Machine Learning.

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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