Deep Causal Learning for Robotic Intelligence
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Abstract (arXiv)
This invited review discusses causal learning in the context of robotic intelligence. The paper introduced the psychological findings on causal learning in human cognition, then it introduced the traditional statistical solutions on causal discovery and causal inference. The paper reviewed recent deep causal learning algorithms with a focus on their architectures and the benefits of using deep nets and discussed the gap between deep causal learning and the needs of robotic intelligence.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Dec 2022.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 1.
3 papers.
- 2024Learning by Watching: A Review of Video-based Learning Approaches for Robot Manipulationcited by 11
- 20233 Dimensional Dense Reconstruction: A Review of Algorithms and Datasetcited by 0
- 2025Bridging the Ex-Vivo to In-Vivo Gap: Synthetic Priors for Monocular Depth Estimation in Specular Surgical Environmentscited by 0
- 2025Bridging the Ex-Vivo to In-Vivo Gap: Synthetic Priors for Monocular Depth Estimation in Specular Surgical Environments29 Dec 2025
- 2024Learning by Watching: A Review of Video-based Learning Approaches for Robot Manipulation11 Feb 2024
- 20233 Dimensional Dense Reconstruction: A Review of Algorithms and Dataset19 Apr 2023