Erik Derner

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研究焦点

主要成就

代表论文

1. 1
   Constructing parsimonious analytic models for dynamic systems via symbolic regression

   25 次引用 · 2020
2. 2
   Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic Regression

   17 次引用 · 2023
3. 3
   Change detection using weighted features for image-based localization

   16 次引用 · 2020
4. 4
   Object-Based Pose Graph for Dynamic Indoor Environments

   12 次引用 · 2020
5. 5
   Reinforcement Learning with Symbolic Input-Output Models

   11 次引用 · 2018
6. 6
   Efficient Object Search Through Probability-Based Viewpoint Selection

   10 次引用 · 2020
7. 7
   Data-driven Construction of Symbolic Process Models for Reinforcement Learning

   9 次引用 · 2018
8. 8
   Selecting Informative Data Samples for Model Learning Through Symbolic Regression

   5 次引用 · 2021
9. 9
   Symbolic Regression for Constructing Analytic Models in Reinforcement Learning

   4 次引用 · 2019
10. 10
    Towards Life-Long Autonomy of Mobile Robots Through Feature-Based Change Detection

    3 次引用 · 2019

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