基本信息
浏览量:65
职业迁徙
个人简介
My past research has covered several areas of machine learning / deep learning, including learning representations and generative models for proteins and peptides, unsupervised and semi-supervised learning with either no or very small amounts of labeled data. I worked on Generative Adversarial Networks (GANs), specifically on finding a better distance metric between the data distribution and the generated distribution, which leads to fast and stable training. I worked on multimodal learning: learning representations across different data modalities like images, text, and speech. And I started my research career working on deep learning approaches to acoustic modeling in speech recognition, bringing advances from the deep learning and computer vision communities to speech recognition.
研究兴趣
论文共 36 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
bioRxiv (Cold Spring Harbor Laboratory) (2022)
引用27浏览0引用
27
0
user-60f947d94c775efc5de23468(2022)
Brian Hie,Salvatore Candido,Zeming Lin ,Ori Kabeli ,Roshan Rao, Nikita Smetanin,Tom Sercu,Alexander Rives
biorxiv (2022)
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