Nate Kohl

1.3k citations
12 papers · 725 · h-index 10

Impact in

Papers in

    • Reinforcement Learning in Robotics 7
    • Evolutionary Algorithms and Applications 6
    • Neural Networks and Applications 4
    • Metaheuristic Optimization Algorithms Research 2
    • Gaussian Processes and Bayesian Inference 2
    • Robotic Locomotion and Control 3

Nate Kohl

11 papers receiving 673 citations

Peers

Nate Kohl
Comparison fields: 5 of 68
  • Artificial Intelligence 481
  • Control and Systems Engineering 158
  • Computer Vision and Pattern Recognition 109
  • Biomedical Engineering 195
  • Computational Theory and Mathematics 50
Replace Danijar Hafner with:
Danijar Hafner United States
Abdeslam Boularias United States
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Athanasios Polydoros Denmark
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Reinaldo A. C. Bianchi Brazil
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Citations per field
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Citations per year

Countries citing papers authored by Nate Kohl

Since Specialization
Citations

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

Fields of papers citing papers by Nate Kohl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Nate Kohl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nate Kohl Line = papers co-authored together Nate Kohl links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2004349
2
Machine learning for fast quadrupedal locomotion
200492
3 200570
4 200560
5 200640
6 200938
7 200537
8 200812
9 200611
10 201211
11
Learning in fractured problems with constructive neural network algorithms
20095
12
Evolving neural networks for strategic decision-making problems
20090

About Nate Kohl

Nate Kohl is a scholar working on Artificial Intelligence, Biomedical Engineering, Automotive Engineering, Aerospace Engineering and Social Psychology, having authored 12 papers that have together received 725 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Evolutionary Algorithms and Applications (6 papers), Neural Networks and Applications (4 papers), Robotic Locomotion and Control (3 papers), Autonomous Vehicle Technology and Safety (2 papers), Metaheuristic Optimization Algorithms Research (2 papers), Gaussian Processes and Bayesian Inference (2 papers) and Hermeneutics and Narrative Identity (1 paper). The work is most often cited by research in Artificial Intelligence (481 citations), Control and Systems Engineering (158 citations), Computer Vision and Pattern Recognition (109 citations), Biomedical Engineering (195 citations) and Computational Theory and Mathematics (50 citations). Nate Kohl has collaborated with scholars based in United States. Frequent co-authors include Peter Stone, Risto Miikkulainen, Kenneth O. Stanley, Shimon Whiteson, Rini Sherony, Risto Miikkulainen, Mohan Sridharan, Nicholas K. Jong and Gregory Kuhlmann. Their work appears in journals such as Robotics and Autonomous Systems, Machine Learning, IEEE Transactions on Evolutionary Computation, Neural Networks and National Conference on Artificial Intelligence.

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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