基本信息
浏览量:142
职业迁徙
个人简介
My life-long goal is to build machines that can acquire common sense without human labeling and can be taught and instructed like humans: by observing how other humans complete tasks, and sometimes with the help of language.I believe common sense comes as a byproduct of using the right biases. For example, for visual understanding, humans have a strong bias on object permanence and most people understand scenes in terms of 3D. That is why we get suprised when a magician pulls a rabbit out of an empty hat. I have developed learning-based methods that are equipped with such biases and these models show strong generality on unseen situations. I have also designed algorithms for machines to learn simple concepts by watching human teachers doing things. Using the acquired knowledge, they are able to imagine their goal, self-supervise their own progress and efficiently pick up skills. I aim at designing learning algorithms that require only natural supervisions, e.g., self-supervision from predicting their raw sensory inputs (e.g., images and videos), supervision from human demonstrations, and priors learned from raw data.
研究兴趣
论文共 40 篇作者统计合作学者相似作者
按年份排序按引用量排序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
arXiv (Cornell University) (2023): 3625-3635
引用0浏览0EIWOS引用
0
0
Journal of Visionno. 9 (2023): 5622-5622
引用0浏览0引用
0
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn