基本信息
views: 1051
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Dr. Dellaert does research in the areas of robotics and computer vision, which present some of the most exciting challenges to anyone interested in artificial intelligence. He is especially keen on Bayesian inference approaches to the difficult inverse problems that keep popping up in these areas. In many cases, exact solutions to these problems are intractable, and as such he is interested in examining whether Monte Carlo (sampling-based) approximations are applicable in those cases.
Since coming to Georgia Tech Dr. Dellaert has explored the theme of probabilistic, model-based reasoning paired with randomized approximation methods in three main research areas:
Advanced sequential Monte Carlo methods
Spatio-Temporal Reconstruction from Images
Simultaneous Localization and Mapping
Since coming to Georgia Tech Dr. Dellaert has explored the theme of probabilistic, model-based reasoning paired with randomized approximation methods in three main research areas:
Advanced sequential Monte Carlo methods
Spatio-Temporal Reconstruction from Images
Simultaneous Localization and Mapping
Research Interests
Papers共 331 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
CoRR (2024)
Cited0Views0EIBibtex
0
0
arxiv(2024)
Cited0Views0Bibtex
0
0
CVPR 2024 (2024)
Cited0Views0Bibtex
0
0
ICRA 2024 (2024)
ICRA 2024 (2024)
Cited0Views0EIBibtex
0
0
IEEE Robotics and Automation Lettersno. 1 (2023): 41-48
CoRR (2023)
Cited0Views0EIBibtex
0
0
2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRApp.3175-3181, (2023)
PLANSpp.755-763, (2023)
CoRR (2022)
Load More
Author Statistics
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn