David Szepesvári

567 total citations
2 papers, 33 citations indexed

About

David Szepesvári is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, David Szepesvári has authored 2 papers receiving a total of 33 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Computer Vision and Pattern Recognition, 1 paper in Artificial Intelligence and 0 papers in Infectious Diseases. Recurrent topics in David Szepesvári's work include Advanced Image and Video Retrieval Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). David Szepesvári is often cited by papers focused on Advanced Image and Video Retrieval Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). David Szepesvári collaborates with scholars based in United Kingdom and Canada. David Szepesvári's co-authors include S. M. Ali Eslami, Yuval Tassa, Geoffrey E. Hinton, Théophane Weber, Koray Kavukcuoglu, Nicolas Heess, Adam White, Richard S. Sutton, B. K. Tanner and Marlos C. Machado and has published in prestigious journals such as Artificial Intelligence.

In The Last Decade

David Szepesvári

2 papers receiving 33 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
David Szepesvári United Kingdom	2	25	13	5	3	2	2	33
Shariq Farooq Bhat Saudi Arabia	3	22 0.9×	7 0.5×	3 0.6×	4 1.3×	1 0.5×	3	27
Didrik Nielsen Denmark	3	15 0.6×	14 1.1×	2 0.4×	2 0.7×		4	23
Yingjie Zhai Australia	2	24 1.0×	8 0.6×	3 0.6×	1 0.3×	3 1.5×	2	31
Maxime Bucher France	2	20 0.8×	8 0.6×	11 2.2×	2 0.7×		2	32
Ronan Sicre France	4	29 1.2×	9 0.7×	3 0.6×		1 0.5×	12	36
Hanxiao Jiang Canada	3	23 0.9×	4 0.3×	6 1.2×	5 1.7×		6	28
Rishabh Kabra United Kingdom	2	17 0.7×	7 0.5×	3 0.6×		1 0.5×	2	20
Emiel Hoogeboom Netherlands	4	18 0.7×	15 1.2×	5 1.0×	1 0.3×		7	31
Qichen Fu United States	3	21 0.8×	4 0.3×	4 0.8×	8 2.7×	1 0.5×	4	28

Countries citing papers authored by David Szepesvári

Since Specialization

Citations

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

Fields of papers citing papers by David Szepesvári

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Szepesvári

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

All Works

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2 of 2 papers shown

1.

Sutton, Richard S., et al.. (2023). Reward-respecting subtasks for model-based reinforcement learning. Artificial Intelligence. 324. 104001–104001. 2 indexed citations

2.

Eslami, S. M. Ali, Nicolas Heess, Théophane Weber, et al.. (2016). Attend, infer, repeat: fast scene understanding with generative models. 29. 3233–3241. 31 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.

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