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Chongli Qin

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On a continuous time model of gradient descent dynamics and instability in deep learning

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Feb 03, 2023
Mihaela Rosca, Yan Wu, Chongli Qin, Benoit Dherin

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Training Generative Adversarial Networks by Solving Ordinary Differential Equations

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Oct 28, 2020
Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andrew Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli

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Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples

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Oct 27, 2020
Sven Gowal, Chongli Qin, Jonathan Uesato, Timothy Mann, Pushmeet Kohli

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Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations

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Dec 06, 2019
Sven Gowal, Chongli Qin, Po-Sen Huang, Taylan Cemgil, Krishnamurthy Dvijotham, Timothy Mann, Pushmeet Kohli

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An Alternative Surrogate Loss for PGD-based Adversarial Testing

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Oct 21, 2019
Sven Gowal, Jonathan Uesato, Chongli Qin, Po-Sen Huang, Timothy Mann, Pushmeet Kohli

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Adversarial Robustness through Local Linearization

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Jul 04, 2019
Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy, Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli

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Verification of Non-Linear Specifications for Neural Networks

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Feb 25, 2019
Chongli Qin, Krishnamurthy, Dvijotham, Brendan O'Donoghue, Rudy Bunel, Robert Stanforth, Sven Gowal, Jonathan Uesato, Grzegorz Swirszcz, Pushmeet Kohli

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On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models

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Nov 05, 2018
Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy Mann, Pushmeet Kohli

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