Search results
Yang Song is a leading expert in generative models, especially score-based diffusion models. He works on improving generative models for diverse modalities, applications, and scientific discovery.
- Blog
Yang Song Toggle navigation. about; cv; publications;...
- Publications
Yang Song*, Sahaj Garg*, Jiaxin Shi, and Stefano Ermon. In...
- Repositories
repositories. Most of my research has code open-sourced at...
- cv
Professional Services. Organizer: NeurIPS 2022 Workshop on...
- Blog
Learn how to generate samples from data distributions by estimating their score functions, which are gradients of log probability density functions. Score-based models have advantages over existing generative models, such as GANs, in terms of sample quality, flexibility, and inverse problem solving.
Yang Song is a Ph.D. student at Stanford University, advised by Stefano Ermon. He has worked as an intern at Google, Uber, and Microsoft, and received several awards and fellowships in AI/ML.
Yang Song. Other names. OpenAI. Verified email at openai.com - Homepage. Machine Learning. Articles 1–20. OpenAI - Cited by 16,679 - Machine Learning.
Yang Song. J Huang, V Rathod, C Sun, M Zhu, A Korattikara, A Fathi, I Fischer, ... Proceedings of the IEEE conference on computer vision and pattern …. Proceedings of the IEEE/CVF conference on computer vision and pattern …. G Van Horn, O Mac Aodha, Y Song, Y Cui, C Sun, A Shepard, H Adam, ...
2022. Articles 1–20. Google Research - Machine Intelligence - Cited by 14,534 - Information Retrieval - Machine Learning - Recommender Systems - Deep Learning - Search Engines.
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral) - yang-song/score_sde
