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Ruiqi Gao's academic website.
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Ruiqi Gao Toggle navigation About (current) Publications CV Ruiqi Gao I am a Research Scientist at Google, Brain team. I am mainly interested in generative models and representation learning. Specifically, I work on efficient and scalable learning algorithms of deep generative models, with an emphasis on energy-based models (EBMs), but also including other types of models. I also work on representational models with implications in neuroscience. I obtained my Ph.D. from UCLA advised by Song-Chun Zhu and Ying Nian Wu . Prior to that, I received my B.S. degree of Statistics from Peking University in China. Contact: ruiqigao at ucla dot edu Highlight research themes: (1) Maximum likelihood learning of deep generative models. Diffusion recovery likelihood of EBMs (Gao et al., ICLR 2021) . Multi-grid learning of EBMs (Gao et al., CVPR 2018) . Spatial-temporal top-down models (Xie*, Gao...
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