Murat Kocaoglu

17 papers receiving 143 citations

Peers

Murat Kocaoglu
Comparison fields: 5 of 38
  • Artificial Intelligence 59
  • Computational Theory and Mathematics 23
  • Biomedical Engineering 60
  • Statistics and Probability 10
  • Computer Networks and Communications 23
Replace Hassaan Saadat with:
Hassaan Saadat Australia
Dina Kamel Belgium
Radek Hrbáček Czechia
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Vivek Kozhikkottu United States
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Themistoklis Haniotakis United States
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Citations per year

Countries citing papers authored by Murat Kocaoglu

Since Specialization
Citations

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

Fields of papers citing papers by Murat Kocaoglu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Murat Kocaoglu, 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 Murat Kocaoglu Line = papers co-authored together Murat Kocaoglu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201330
2 201722
3
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
201915
4
Experimental Design for Learning Causal Graphs with Latent Variables
201713
5 201213
6 201213
7 201313
8
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
20209
9 20145
10 20124
11 20143
12
Cost-Optimal Learning of Causal Graphs
20173
13
Sample Efficient Active Learning of Causal Trees
20192
14
Active Structure Learning of Causal DAGs via Directed Clique Trees
20202
15 20162
16 20182
17
A Smoothed Analysis for Learning Sparse Polynomials.
20141
18 20240
19 20150
20 20130

About Murat Kocaoglu

Murat Kocaoglu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering, Statistics and Probability and Computer Networks and Communications, having authored 20 papers that have together received 152 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (8 papers), Machine Learning and Algorithms (7 papers), Molecular Communication and Nanonetworks (6 papers), Energy Harvesting in Wireless Networks (4 papers), Wireless Body Area Networks (4 papers), Rough Sets and Fuzzy Logic (2 papers), Algorithms and Data Compression (2 papers) and Sparse and Compressive Sensing Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (59 citations), Computational Theory and Mathematics (23 citations), Biomedical Engineering (60 citations), Statistics and Probability (10 citations) and Computer Networks and Communications (23 citations). Murat Kocaoglu has collaborated with scholars based in United States, Türkiye and Netherlands. Frequent co-authors include Özgür B. Akan, Karthikeyan Shanmugam, Derya Malak, Elias Bareinboim, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi, Burhan Gülbahar, Dmitriy Katz and Kristjan Greenewald. Their work appears in journals such as Computer, IEEE Systems Journal, IEEE Transactions on Nanotechnology, IEEE Transactions on Wireless Communications and Nano Communication Networks.

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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