Sven Magg

1.0k total citations
22 papers, 468 citations indexed

About

Sven Magg is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sven Magg has authored 22 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Control and Systems Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sven Magg's work include Reinforcement Learning in Robotics (8 papers), Robot Manipulation and Learning (5 papers) and Speech and Audio Processing (3 papers). Sven Magg is often cited by papers focused on Reinforcement Learning in Robotics (8 papers), Robot Manipulation and Learning (5 papers) and Speech and Audio Processing (3 papers). Sven Magg collaborates with scholars based in Germany, Chile and United Kingdom. Sven Magg's co-authors include Stefan Wermter, Henrique Siqueira, Francisco Cruz, Cornelius Weber, German I. Parisi, Sebastian Starke, Jianwei Zhang, Norman Hendrich, Stefan Heinrich and Erik Strahl and has published in prestigious journals such as Neural Networks, Neural Computing and Applications and International Journal of Social Robotics.

In The Last Decade

Sven Magg

22 papers receiving 450 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sven Magg Germany	11	204	178	124	111	78	22	468
Mengtian Zhou China	7	117 0.6×	219 1.2×	244 2.0×	53 0.5×	90 1.2×	9	477
Fernándo Alonso-Martín Spain	14	181 0.9×	100 0.6×	70 0.6×	90 0.8×	209 2.7×	38	485
Mariacarla Staffa Italy	12	192 0.9×	92 0.5×	39 0.3×	80 0.7×	153 2.0×	53	479
Ignazio Infantino Italy	13	173 0.8×	153 0.9×	46 0.4×	175 1.6×	96 1.2×	60	446
Matthias Kerzel Germany	12	149 0.7×	101 0.6×	36 0.3×	91 0.8×	68 0.9×	43	380
Mark Elshaw United Kingdom	11	81 0.4×	141 0.8×	102 0.8×	45 0.4×	87 1.1×	23	350
Masayoshi Kanoh Japan	11	182 0.9×	96 0.5×	65 0.5×	169 1.5×	287 3.7×	106	474
Deepak Gopinath United States	5	130 0.6×	64 0.4×	53 0.4×	55 0.5×	59 0.8×	10	302
Kotaro Funakoshi Japan	15	454 2.2×	136 0.8×	61 0.5×	89 0.8×	172 2.2×	100	639
Frank Wallhoff Germany	14	189 0.9×	301 1.7×	117 0.9×	90 0.8×	96 1.2×	69	670

Countries citing papers authored by Sven Magg

Since Specialization

Citations

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

Fields of papers citing papers by Sven Magg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sven Magg

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

All Works

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20 of 20 papers shown

Magg, Sven, et al.. (2023). Multimodal video retrieval with CLIP: a user study. Information Retrieval. 26(1-2). 4 indexed citations

Lu, Wenhao, et al.. (2023). A Closer Look at Reward Decomposition for High-Level Robotic Explanations. 429–436. 1 indexed citations

Magg, Sven, et al.. (2022). Hierarchical goals contextualize local reward decomposition explanations. Neural Computing and Applications. 35(23). 16693–16704. 8 indexed citations

Andriella, Antonio, Henrique Siqueira, Di Fu, et al.. (2020). Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits. International Journal of Social Robotics. 13(8). 2081–2102. 33 indexed citations

Siqueira, Henrique, Sven Magg, & Stefan Wermter. (2020). Efficient Facial Feature Learning with Wide Ensemble-Based Convolutional Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 5800–5809. 115 indexed citations

Cruz, Francisco, Sven Magg, Yukie Nagai, & Stefan Wermter. (2018). Improving interactive reinforcement learning: What makes a good teacher?. Connection Science. 30(3). 306–325. 21 indexed citations

Siqueira, Henrique, et al.. (2018). Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue. 1–9. 5 indexed citations

Siqueira, Henrique, Pablo Barros, Sven Magg, & Stefan Wermter. (2018). An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions. 521. 1563–1568. 7 indexed citations

Magg, Sven, et al.. (2018). Deep reinforcement learning using compositional representations for performing instructions. Paladyn Journal of Behavioral Robotics. 9(1). 358–373. 1 indexed citations

10.

Weber, Cornelius, et al.. (2017). Reusing Neural Speech Representations for Auditory Emotion Recognition. International Joint Conference on Natural Language Processing. 1. 423–430. 10 indexed citations

11.

Kerzel, Matthias, Erik Strahl, Sven Magg, et al.. (2017). NICO — Neuro-inspired companion: A developmental humanoid robot platform for multimodal interaction. 113–120. 47 indexed citations

12.

Cruz, Francisco, et al.. (2017). Agent-advising approaches in an interactive reinforcement learning scenario. 8 indexed citations

13.

Starke, Sebastian, Norman Hendrich, Sven Magg, & Jianwei Zhang. (2016). An efficient hybridization of Genetic Algorithms and Particle Swarm Optimization for inverse kinematics. 1782–1789. 35 indexed citations

14.

Cruz, Francisco, Sven Magg, Cornelius Weber, & Stefan Wermter. (2016). Training Agents With Interactive Reinforcement Learning and Contextual Affordances. IEEE Transactions on Cognitive and Developmental Systems. 8(4). 271–284. 58 indexed citations

15.

Parisi, German I., Sven Magg, & Stefan Wermter. (2016). Human motion assessment in real time using recurrent self-organization. 71–76. 35 indexed citations

16.

Magg, Sven, et al.. (2015). Attention modeled as information in learning multisensory integration. Neural Networks. 65. 44–52. 10 indexed citations

17.

Cruz, Francisco, et al.. (2015). Interactive reinforcement learning through speech guidance in a domestic scenario. 1–8. 28 indexed citations

18.

Parisi, German I., et al.. (2015). Learning human motion feedback with neural self-organization. 1–6. 10 indexed citations

19.

Cruz, Francisco, Sven Magg, Cornelius Weber, & Stefan Wermter. (2014). Improving reinforcement learning with interactive feedback and affordances. 5. 165–170. 9 indexed citations

20.

Magg, Sven. (2007). Pattern Formation in Homogeneous and Heterogeneous Swarms: Differences Between Versatile and Specialized Agents. 311–316. 9 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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