Christian Szegedy

129.0k total citations · 6 hit papers
25 papers, 56.1k citations indexed

About

Christian Szegedy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture. According to data from OpenAlex, Christian Szegedy has authored 25 papers receiving a total of 56.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Hardware and Architecture. Recurrent topics in Christian Szegedy's work include VLSI and FPGA Design Techniques (6 papers), Topic Modeling (5 papers) and Low-power high-performance VLSI design (5 papers). Christian Szegedy is often cited by papers focused on VLSI and FPGA Design Techniques (6 papers), Topic Modeling (5 papers) and Low-power high-performance VLSI design (5 papers). Christian Szegedy collaborates with scholars based in United States, Germany and Poland. Christian Szegedy's co-authors include Vincent Vanhoucke, Sergey Ioffe, Dumitru Erhan, Zbigniew Wojna, Dragomir Anguelov, Andrew Rabinovich, Scott Reed, Wei Liu, Pierre Sermanet and Yangqing Jia and has published in prestigious journals such as ACM SIGPLAN Notices, Discrete Applied Mathematics and Computational Optimization and Applications.

In The Last Decade

Christian Szegedy

24 papers receiving 54.0k citations

Hit Papers

Going deeper with convolutions 2013 2026 2017 2021 2015 2016 2017 2014 2013 10.0k 20.0k 30.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christian Szegedy United States 12 30.6k 18.2k 7.2k 4.8k 4.1k 25 56.1k
Karen Simonyan United States 23 34.0k 1.1× 21.1k 1.2× 5.6k 0.8× 5.6k 1.2× 3.4k 0.8× 49 63.3k
Vincent Vanhoucke United States 19 30.8k 1.0× 23.2k 1.3× 7.3k 1.0× 4.8k 1.0× 4.3k 1.0× 37 62.8k
Jia Deng United States 32 40.9k 1.3× 25.2k 1.4× 6.2k 0.9× 5.3k 1.1× 3.2k 0.8× 61 65.0k
Alex Krizhevsky Canada 7 31.3k 1.0× 24.9k 1.4× 6.1k 0.8× 5.3k 1.1× 4.7k 1.1× 7 70.5k
Yangqing Jia United States 24 27.0k 0.9× 14.2k 0.8× 4.2k 0.6× 4.4k 0.9× 2.7k 0.7× 39 44.1k
Dumitru Erhan United States 18 23.5k 0.8× 14.2k 0.8× 4.1k 0.6× 3.4k 0.7× 2.4k 0.6× 22 40.3k
Zheng Zhang China 68 21.1k 0.7× 11.3k 0.6× 4.0k 0.5× 4.9k 1.0× 3.2k 0.8× 684 44.4k
Trevor Darrell United States 84 54.3k 1.8× 24.0k 1.3× 5.2k 0.7× 7.5k 1.6× 4.9k 1.2× 389 78.9k
Bernhard Schölkopf Germany 96 23.7k 0.8× 31.3k 1.7× 3.2k 0.4× 5.1k 1.1× 4.4k 1.1× 583 79.6k
Dragomir Anguelov United States 30 21.5k 0.7× 10.5k 0.6× 3.7k 0.5× 3.2k 0.7× 2.3k 0.6× 57 37.3k

Countries citing papers authored by Christian Szegedy

Since Specialization
Citations

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

Fields of papers citing papers by Christian Szegedy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christian Szegedy

This figure shows the co-authorship network connecting the top 25 collaborators of Christian Szegedy. A scholar is included among the top collaborators of Christian Szegedy 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 Christian Szegedy. Christian Szegedy 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
1.
Kaiser, Łukasz, et al.. (2022). Hierarchical Transformers Are More Efficient Language Models. 1559–1571. 20 indexed citations
2.
Rabe, Markus N., Dennis Lee, Kshitij Bansal, & Christian Szegedy. (2021). Mathematical Reasoning via Self-supervised Skip-tree Training. International Conference on Learning Representations. 3 indexed citations
3.
Lee, Dennis, Christian Szegedy, Markus N. Rabe, Sarah M. Loos, & Kshitij Bansal. (2020). Mathematical Reasoning in Latent Space. International Conference on Learning Representations. 4 indexed citations
4.
Rabe, Markus N., Dennis Lee, Kshitij Bansal, & Christian Szegedy. (2020). Language Modeling for Formal Mathematics. arXiv (Cornell University). 1 indexed citations
5.
Bansal, Kshitij, et al.. (2019). HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving. International Conference on Machine Learning. 454–463. 21 indexed citations
6.
Bansal, Kshitij, et al.. (2019). HOList: An Environment for Machine Learning of Higher-Order Theorem Proving (extended version). arXiv (Cornell University). 2 indexed citations
7.
Alemi, Alexander A., François Chollet, Geoffrey Irving, Christian Szegedy, & Josef Urban. (2016). DeepMath - Deep Sequence Models for Premise Selection. Neural Information Processing Systems. 29. 2235–2243. 15 indexed citations
8.
Szegedy, Christian, Wei Liu, Yangqing Jia, et al.. (2015). Going deeper with convolutions. 1–9. 30609 indexed citations breakdown →
9.
Reed, Scott, Honglak Lee, Dragomir Anguelov, et al.. (2015). TRAINING DEEP NEURAL NETWORKS ON NOISY LABELS WITH BOOTSTRAPPING. arXiv (Cornell University). 145 indexed citations
10.
Toshev, Alexander & Christian Szegedy. (2014). DeepPose: Human Pose Estimation via Deep Neural Networks. arXiv (Cornell University). 1653–1660. 1832 indexed citations breakdown →
11.
Erhan, Dumitru, Christian Szegedy, Alexander Toshev, & Dragomir Anguelov. (2014). Scalable Object Detection Using Deep Neural Networks. 2155–2162. 723 indexed citations breakdown →
12.
Szegedy, Christian, Alexander Toshev, & Dumitru Erhan. (2013). Deep Neural Networks for Object Detection. Neural Information Processing Systems. 26. 2553–2561. 774 indexed citations breakdown →
13.
Lublinerman, Roberto, Christian Szegedy, & Stavros Tripakis. (2009). Modular code generation from synchronous block diagrams. 78–89. 34 indexed citations
14.
Rautenbach, Dieter, et al.. (2007). Timing optimization by restructuring long combinatorial paths. International Conference on Computer Aided Design. 536–543. 8 indexed citations
15.
Rautenbach, Dieter & Christian Szegedy. (2007). A class of problems for which cyclic relaxation converges linearly. Computational Optimization and Applications. 41(1). 53–60. 2 indexed citations
16.
Rautenbach, Dieter, et al.. (2007). On the cost of optimal alphabetic code trees with unequal letter costs. European Journal of Combinatorics. 29(2). 386–394. 1 indexed citations
17.
Szegedy, Christian, et al.. (2007). A morphing approach to address placement stability. 95–102. 1 indexed citations
18.
Rautenbach, Dieter, et al.. (2007). Timing optimization by restructuring long combinatorial paths. Digest of technical papers/Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design. 536–543. 7 indexed citations
19.
Rautenbach, Dieter, et al.. (2005). Delay optimization of linear depth boolean circuits with prescribed input arrival times. Journal of Discrete Algorithms. 4(4). 526–537. 8 indexed citations
20.
Szegedy, Christian. (2002). On the Number of 3-Edge Colorings of Cubic Graphs. European Journal of Combinatorics. 23(1). 113–120. 3 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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