Stefan Elfwing

2.4k total citations · 1 hit paper
18 papers, 1.3k citations indexed

About

Stefan Elfwing is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Stefan Elfwing has authored 18 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 3 papers in Cognitive Neuroscience and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Stefan Elfwing's work include Reinforcement Learning in Robotics (12 papers), Evolutionary Algorithms and Applications (7 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Stefan Elfwing is often cited by papers focused on Reinforcement Learning in Robotics (12 papers), Evolutionary Algorithms and Applications (7 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Stefan Elfwing collaborates with scholars based in Japan, Sweden and United States. Stefan Elfwing's co-authors include Eiji Uchibe, Kenji Doya, Henrik I. Christensen, Ben Seymour, Geert Litjens, Jeroen van der Laak, Jasper Linmans, John Öhrvik, Maziar Nikberg and Dorota Johansson and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Evolutionary Computation and Neural Networks.

In The Last Decade

Stefan Elfwing

18 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Sigmoid-weighted linear units for neural network function approximation in reinforcement learning

2018 1.1k citations Stefan Elfwing, Eiji Uchibe et al. Neural Networks profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stefan Elfwing Japan	11	505	451	107	97	89	18	1.3k
Derek Rose United States	12	442 0.9×	635 1.4×	161 1.5×	55 0.6×	104 1.2×	29	1.6k
Tian-Xing Xu China	5	706 1.4×	347 0.8×	114 1.1×	103 1.1×	128 1.4×	12	1.5k
Jyri Kivinen United Kingdom	6	663 1.3×	646 1.4×	116 1.1×	39 0.4×	82 0.9×	8	1.5k
Yun Xiao China	14	829 1.6×	675 1.5×	133 1.2×	96 1.0×	85 1.0×	60	1.8k
Saurabh Singh India	7	617 1.2×	610 1.4×	74 0.7×	58 0.6×	150 1.7×	12	1.4k
Dipti Prasad Mukherjee India	19	746 1.5×	377 0.8×	77 0.7×	138 1.4×	111 1.2×	76	1.4k
Brian C. Van Essen United States	6	283 0.6×	340 0.8×	144 1.3×	47 0.5×	132 1.5×	10	1.2k
Stefan Westberg United States	3	282 0.6×	334 0.7×	130 1.2×	51 0.5×	130 1.5×	6	1.2k
Qinghe Zheng China	17	477 0.9×	423 0.9×	162 1.5×	31 0.3×	137 1.5×	39	1.3k
Lei Cai China	19	471 0.9×	427 0.9×	57 0.5×	112 1.2×	38 0.4×	99	1.2k

Countries citing papers authored by Stefan Elfwing

Since Specialization

Citations

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

Fields of papers citing papers by Stefan Elfwing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefan Elfwing

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

All Works

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18 of 18 papers shown

Johansson, Dorota, et al.. (2023). Evaluation of A Computer-Aided Detection Software for Prostate Cancer Prediction: Excellent Diagnostic Accuracy Independent of Preanalytical Factors. Laboratory Investigation. 103(12). 100257–100257. 2 indexed citations

Elfwing, Stefan, et al.. (2023). A Deep Neural Network–Based Decision Support Tool for the Detection of Lymph Node Metastases in Colorectal Cancer Specimens. Modern Pathology. 36(2). 100015–100015. 8 indexed citations

Linmans, Jasper, Stefan Elfwing, Jeroen van der Laak, & Geert Litjens. (2022). Predictive uncertainty estimation for out-of-distribution detection in digital pathology. Medical Image Analysis. 83. 102655–102655. 34 indexed citations

Elfwing, Stefan, et al.. (2020). Modular deep reinforcement learning from reward and punishment for robot navigation. Neural Networks. 135. 115–126. 40 indexed citations

Elfwing, Stefan, Eiji Uchibe, & Kenji Doya. (2018). Sigmoid-weighted linear units for neural network function approximation in reinforcement learning. Neural Networks. 107. 3–11. 1064 indexed citations breakdown →

Elfwing, Stefan, et al.. (2018). Deep Reinforcement Learning by Parallelizing Reward and Punishment using the MaxPain Architecture. 175–180. 7 indexed citations

Elfwing, Stefan, Eiji Uchibe, & Kenji Doya. (2018). Online meta-learning by parallel algorithm competition. Proceedings of the Genetic and Evolutionary Computation Conference. 426–433. 10 indexed citations

Elfwing, Stefan & Ben Seymour. (2017). Parallel reward and punishment control in humans and robots: Safe reinforcement learning using the MaxPain algorithm. Apollo (University of Cambridge). 140–147. 19 indexed citations

Elfwing, Stefan, Eiji Uchibe, & Kenji Doya. (2016). From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning. Neural Networks. 84. 17–27. 10 indexed citations

10.

Elfwing, Stefan & Kenji Doya. (2014). Emergence of Polymorphic Mating Strategies in Robot Colonies. PLoS ONE. 9(4). e93622–e93622. 6 indexed citations

11.

Elfwing, Stefan, Eiji Uchibe, & Kenji Doya. (2014). Expected energy-based restricted Boltzmann machine for classification. Neural Networks. 64. 29–38. 25 indexed citations

12.

Elfwing, Stefan, Eiji Uchibe, & Kenji Doya. (2013). Scaled free-energy based reinforcement learning for robust and efficient learning in high-dimensional state spaces. Frontiers in Neurorobotics. 7. 3–3. 9 indexed citations

13.

Elfwing, Stefan, Eiji Uchibe, Kenji Doya, & Henrik I. Christensen. (2011). Darwinian embodied evolution of the learning ability for survival. Adaptive Behavior. 19(2). 101–120. 15 indexed citations

14.

Elfwing, Stefan, Eiji Uchibe, Kenji Doya, & Henrik I. Christensen. (2008). Co-evolution of Shaping Rewards and Meta-Parameters in Reinforcement Learning. Adaptive Behavior. 16(6). 400–412. 17 indexed citations

15.

Elfwing, Stefan. (2007). Embodied Evolution of Learning Ability. KTH Publication Database DiVA (KTH Royal Institute of Technology). 7 indexed citations

16.

Elfwing, Stefan, Eiji Uchibe, Kenji Doya, & Henrik I. Christensen. (2007). Evolutionary Development of Hierarchical Learning Structures. IEEE Transactions on Evolutionary Computation. 11(2). 249–264. 15 indexed citations

17.

Elfwing, Stefan, Eiji Uchibe, Kenji Doya, & Henrik I. Christensen. (2005). Multi-agent reinforcement learning: using macro actions to learn a mating task. 4. 3164–3169. 11 indexed citations

18.

Elfwing, Stefan, Eiji Uchibe, Kenji Doya, & Henrik I. Christensen. (2005). Biologically Inspired Embodied Evolution of Survival. 3. 2210–2216. 22 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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