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Chongli Qin
Chongli Qin
Research Scientist, DeepMind
Verified email at google.com
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Cited by
Cited by
Year
Improved protein structure prediction using potentials from deep learning
AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ...
Nature 577 (7792), 706-710, 2020
19912020
On the effectiveness of interval bound propagation for training verifiably robust models
S Gowal, K Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ...
arXiv preprint arXiv:1810.12715, 2018
3182018
Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)
AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ...
Proteins: Structure, Function, and Bioinformatics 87 (12), 1141-1148, 2019
2372019
Adversarial robustness through local linearization
C Qin, J Martens, S Gowal, D Krishnan, K Dvijotham, A Fawzi, S De, ...
Advances in Neural Information Processing Systems 32, 2019
2092019
Uncovering the limits of adversarial training against norm-bounded adversarial examples
S Gowal, C Qin, J Uesato, T Mann, P Kohli
arXiv preprint arXiv:2010.03593, 2020
1582020
De novo structure prediction with deeplearning based scoring
R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, A Zidek, ...
Annu Rev Biochem 77 (363-382), 6, 2018
1282018
Scalable verified training for provably robust image classification
S Gowal, KD Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
872019
Power law tails in phylogenetic systems
C Qin, LJ Colwell
Proceedings of the National Academy of Sciences 115 (4), 690-695, 2018
562018
An alternative surrogate loss for pgd-based adversarial testing
S Gowal, J Uesato, C Qin, PS Huang, T Mann, P Kohli
arXiv preprint arXiv:1910.09338, 2019
542019
Achieving robustness in the wild via adversarial mixing with disentangled representations
S Gowal, C Qin, PS Huang, T Cemgil, K Dvijotham, T Mann, P Kohli
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
402020
Verification of non-linear specifications for neural networks
C Qin, B O'Donoghue, R Bunel, R Stanforth, S Gowal, J Uesato, ...
arXiv preprint arXiv:1902.09592, 2019
332019
A framework for robustness certification of smoothed classifiers using f-divergences
KD Dvijotham, J Hayes, B Balle, Z Kolter, C Qin, A Gyorgy, K Xiao, ...
302020
Efficient neural network verification with exactness characterization
KD Dvijotham, R Stanforth, S Gowal, C Qin, S De, P Kohli
Uncertainty in artificial intelligence, 497-507, 2020
232020
Training generative adversarial networks by solving ordinary differential equations
C Qin, Y Wu, JT Springenberg, A Brock, J Donahue, T Lillicrap, P Kohli
Advances in Neural Information Processing Systems 33, 5599-5609, 2020
212020
Augustin ˇZıdek, Alexander WR Nelson, Alex Bridgland, Hugo Penedones, Stig Petersen, Karen Simonyan, Steve Crossan, Pushmeet Kohli, David T. Jones, David Silver, Koray …
AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin
Nature 577 (7792), 706-710, 2020
152020
On the effectiveness of interval bound propagation for training verifiably robust models (2018)
S Gowal, K Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ...
arXiv preprint arXiv:1810.12715, 2018
132018
Machine learning for determining protein structures
AW Senior, J Kirkpatrick, L Sifre, RA Evans, H Penedones, C Qin, R Sun, ...
US Patent App. 17/266,724, 2021
12021
Machine learning for determining protein structures
AW Senior, J Kirkpatrick, L Sifre, RA Evans, H Penedones, C Qin, R Sun, ...
US Patent App. 17/266,689, 2021
2021
Stable and efficient training of adversarial models by an iterated update operation of second order or higher
C Qin, Y Wu
US Patent App. 17/337,376, 2021
2021
Machine learning for determining protein structures
AW Senior, J Kirkpatrick, L Sifre, RA Evans, H Penedones, C Qin, R Sun, ...
US Patent App. 17/265,708, 2021
2021
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