Robustness Of Deep Neural Networks Professors in Global

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Mikhail Glazunov
Delft University of Technology Netherlands
robustness of deep neural networks
deep learning
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Zico Kolter
Carnegie Mellon University United States of America
robustness of algorithms
deep learning
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Yaoliang Yu
University of Waterloo Canada
robustness
robust stochastic optimization
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Kimberly Villalobos Carballo
New York University United States of America
robustness
deep learning
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Hassan Sajjad
Dalhousie University Canada
robustness
deep learning
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Chaoyue Zhao
University of Washington United States of America
robust optimization
deep reinforcement learning
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Anshuk Uppal
Technical University of Denmark Denmark
uncertainty robustness
deep learning
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Cassio De Campos
Eindhoven University of Technology Belgium
robust artificial intelligence
reliable machine learning
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Tobias Eifler
Technical University of Denmark Denmark
structural robustness
robust design
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Nathaniel Bastian
Pennsylvania State University United States of America
robust learning
deep learning
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Nina Taherimakhsousi
University of Victoria Canada
deep reinforcement learning
deep learning
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Kin-choong Yow
University of Regina Canada
deep reinforcement learning
deep learning
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Kevin Luck
Vrije Universiteit Amsterdam Netherlands
deep reinforcement learning
deep learning
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Arthur Jacot
New York University United States of America
training dynamics of deep neural networks
deep learning
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Yarin Gal
University of Oxford United Kingdom
deep reinforcement learning
deep probabilistic ai
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Hon Kwan
University of Windsor Canada
deep neural network design
deep learning
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Qiang Liu
University of Texas at Austin United States of America
deep reinforcement learning
deep distributed learning
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Ilias Diakonikolas
University of Wisconsin–Madison United States of America
high-dimensional robust statistics
foundations of deep learning
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Sebastian Denzler
Friedrich-Alexander-Universität Erlangen-Nürnberg Germany
robust bayesian optimization
distributionally robust optimization
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Mårten Wadenbäck
Linköping University Sweden
robust feature matching
deep learning
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Rasmus Paulsen
Technical University of Denmark Denmark
deep reinforcement learning
geometric deep learning
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