Martin Mladenov

31 papers receiving 319 citations

Peers

Martin Mladenov
Comparison fields: 5 of 66
  • Artificial Intelligence 158
  • Computer Vision and Pattern Recognition 95
  • Electrical and Electronic Engineering 75
  • Signal Processing 49
  • Computer Networks and Communications 43
Replace Ling Xiao with:
Ling Xiao China
Mengyuan Wang China
L. V. Subramaniam India
Hadi Tabatabaee Malazi Iran
Kyosuke Nishida Japan
Kyoungsoo Bok South Korea
Jibing Gong China
Fei Yi China
Arti Arya India
Martin Mladenov relative to Ling Xiao China Ling Xiao's profile →
Citations per field
00.5×3.8×
Ling Xiao · 1×
Citations per year

Countries citing papers authored by Martin Mladenov

Since Specialization
Citations

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

Fields of papers citing papers by Martin Mladenov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Mladenov

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Mladenov. A scholar is included among the top collaborators of Martin Mladenov 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 Martin Mladenov. Martin Mladenov 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 2
3 2
4 2
5 11
6
Differentiable Meta-Learning in Contextual Bandits.
1
7
Differentiable Meta-Learning of Bandit Policies.
4
8 1
9 6
10 2
11 2
12
RELOOP: A Python-Embedded Declarative Language for Relational Optimization.
2
13
Equitable partitions of concave free energies
4
14
Computer science on the move: inferring migration regularities from the web via compressed label propagation
4
15 11
16
Lifted message passing as reparametrization of graphical models
9
17
Lifted inference via k-locality
2
18 17
19 13
20 26

About Martin Mladenov

Martin Mladenov is a scholar working on Management Science and Operations Research, Artificial Intelligence and Geography, Planning and Development, having authored 32 papers that have together received 332 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (10 papers), Machine Learning and Algorithms (6 papers) and Advanced Bandit Algorithms Research (6 papers). The work is most often cited by research in Transportation (36 citations), Artificial Intelligence (158 citations) and Computer Vision and Pattern Recognition (95 citations). Martin Mladenov has collaborated with scholars based in Germany, United States and Canada. Frequent co-authors include Michael Möck, Kristian Kersting, Babak Ahmadi, Gennady Andrienko, Natalia Andrienko, Sriraam Natarajan, Amir Globerson, Craig Boutilier, Pavel Tokmakov and Roman Garnett. Their work appears in journals such as Artificial Intelligence, Machine Learning and IEEE Transactions on Visualization and Computer Graphics.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026