Christian Szegedy
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Going deeper with convolutions
C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ...
Proceedings of the IEEE conference on computer vision and pattern…, 2015
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S Ioffe, C Szegedy
International conference on machine learning, 448-456, 2015
Ssd: Single shot multibox detector
W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg
European conference on computer vision, 21-37, 2016
Rethinking the inception architecture for computer vision
C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna
Proceedings of the IEEE conference on computer vision and pattern…, 2016
Explaining and harnessing adversarial examples
IJ Goodfellow, J Shlens, C Szegedy
arXiv preprint arXiv:1412.6572, 2014
Inception-v4, inception-resnet and the impact of residual connections on learning
C Szegedy, S Ioffe, V Vanhoucke, AA Alemi
Thirty-first AAAI conference on artificial intelligence, 2017
Intriguing properties of neural networks
C Szegedy, W Zaremba, I Sutskever, J Bruna, D Erhan, I Goodfellow, ...
arXiv preprint arXiv:1312.6199, 2013
Deeppose: Human pose estimation via deep neural networks
A Toshev, C Szegedy
Proceedings of the IEEE conference on computer vision and pattern…, 2014
Deep neural networks for object detection
C Szegedy, A Toshev, D Erhan
Scalable object detection using deep neural networks
D Erhan, C Szegedy, A Toshev, D Anguelov
Proceedings of the IEEE conference on computer vision and pattern…, 2014
Training deep neural networks on noisy labels with bootstrapping
S Reed, H Lee, D Anguelov, C Szegedy, D Erhan, A Rabinovich
arXiv preprint arXiv:1412.6596, 2014
Scalable, high-quality object detection
C Szegedy, S Reed, D Erhan, D Anguelov, S Ioffe
arXiv preprint arXiv:1412.1441, 2014
Deepmath-deep sequence models for premise selection
G Irving, C Szegedy, AA Alemi, N En, F Chollet, J Urban
Advances in Neural Information Processing Systems 29, 2235-2243, 2016
Deep network guided proof search
S Loos, G Irving, C Szegedy, C Kaliszyk
arXiv preprint arXiv:1701.06972, 2017
Modular code generation from synchronous block diagrams: modularity vs. code size
R Lublinerman, C Szegedy, S Tripakis
Proceedings of the 36th annual ACM SIGPLAN-SIGACT symposium on Principles of…, 2009
Object detection using deep neural networks
C Szegedy, D Erhan, AT Toshev
US Patent 9,275,308, 2016
HOList: An environment for machine learning of higher order logic theorem proving
K Bansal, S Loos, M Rabe, C Szegedy, S Wilcox
International Conference on Machine Learning, 454-463, 2019
Holstep: A machine learning dataset for higher-order logic theorem proving
C Kaliszyk, F Chollet, C Szegedy
arXiv preprint arXiv:1703.00426, 2017
Graph representations for higher-order logic and theorem proving
A Paliwal, S Loos, M Rabe, K Bansal, C Szegedy
Proceedings of the AAAI Conference on Artificial Intelligence 34 (03), 2967-2974, 2020
Processing images using deep neural networks
C Szegedy, VO Vanhoucke
US Patent 9,715,642, 2017
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