Qin, Chongli

7 publications

NeurIPS 2023 Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples Marco Jiralerspong, Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, Gauthier Gidel

TMLR 2023 On a Continuous Time Model of Gradient Descent Dynamics and Instability in Deep Learning Mihaela Rosca, Yan Wu, Chongli Qin, Benoit Dherin

ICLR 2020 A Framework for Robustness Certification of Smoothed Classifiers Using F-Divergences Krishnamurthy Dvijotham, Jamie Hayes, Borja Balle, Zico Kolter, Chongli Qin, Andras Gyorgy, Kai Xiao, Sven Gowal, Pushmeet Kohli

NeurIPS 2020 Training Generative Adversarial Networks by Solving Ordinary Differential Equations Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andy Brock, Jeff Donahue, Timothy Lillicrap, Pushmeet Kohli

NeurIPS 2019 Adversarial Robustness Through Local Linearization Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli

UAI 2019 Efficient Neural Network Verification with Exactness Characterization Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli

ICLR 2019 Verification of Non-Linear Specifications for Neural Networks Chongli Qin, Krishnamurthy Dvijotham, Brendan O'Donoghue, Rudy Bunel, Robert Stanforth, Sven Gowal, Jonathan Uesato, Grzegorz Swirszcz, Pushmeet Kohli