Generative 3d Deep Learning Professors in Global

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Yi Fang
New York University Tandon School of Engineering United States of America
3d deep learning
3d meta-learning
3d vision-based ai
3d computer vision
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Amos Storkey
University of Edinburgh United Kingdom
generative ai
generative models
deep learning
machine learning
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Saeed Anwar
University of Western Australia Australia
generative ai
deep learning
3d vision
machine learning
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Kin-choong Yow
University of Regina Canada
deep learning
generative adversarial networks
deep reinforcement learning
machine learning
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Paul Henderson
University of Glasgow United Kingdom
generative ai
3d computer vision
machine learning
probabilistic machine learning
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Fergus Nevill
New York University United States of America
generative models
deep learning
machine learning
representation learning
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Molei Tao
Georgia Institute of Technology United States of America
generative modeling
deep learning theory
machine learning
probabilistic machine learning
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Yaoliang Yu
University of Waterloo Canada
generative modelling
distributed learning
machine learning
representation learning
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Honglak Lee
University of Michigan United States of America
deep learning
large-scale learning
machine learning
representation learning
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
deep probabilistic ai
machine learning
bayesian deep learning
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Angela Dai
Technical University of Munich Germany
generative 3d deep learning
3d understanding
3d reconstruction
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Jingmin Huang
University of Southampton United Kingdom
deep generative models
deep learning
machine learning
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Jelmer Wolterink
University of Twente Netherlands
generative models
geometric deep learning
machine learning
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Ingo Ziegler
University of Copenhagen Denmark
generative modeling
synthetic data generation
representation learning
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Jan Gerken
University of Gothenburg Sweden
generative models
geometric deep learning
machine learning
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Pouria Rouzrokh
Yale University United States of America
generative artificial intelligence
deep learning
machine learning
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Lingjie Liu
University of Pennsylvania United States of America
3d generative models
3d reconstruction
neural rendering
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Mikhail Glazunov
Delft University of Technology Netherlands
generative modeling
deep learning
bayesian deep learning
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Sriram Subramanian
Carleton University Canada
generative ai
deep learning
machine learning
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Garrett Morris
University of Oxford United Kingdom
generative ai
deep learning
machine learning
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Amir Razavi
University of Ottawa Canada
generative ai
deep learning
machine learning
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