| TensorFlow: Large-scale machine learning on heterogeneous systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... | 26402* | 2015 |
| 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 | 12243 | 2016 |
| Explaining and harnessing adversarial examples I Goodfellow, J Shlens, C Szegedy ICLR, 2014 | 6955 | 2014 |
| A tutorial on principal component analysis J Shlens arXiv preprint arXiv:1404.1100, 2014 | 2962 | 2014 |
| Learning transferable architectures for scalable image recognition B Zoph, V Vasudevan, J Shlens, QV Le Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 2453 | 2018 |
| Devise: A deep visual-semantic embedding model A Frome, G Corrado, J Shlens, S Bengio, J Dean, MA Ranzato, T Mikolov | 1874 | 2013 |
| Conditional image synthesis with auxiliary classifier gans A Odena, C Olah, J Shlens International conference on machine learning, 2642-2651, 2017 | 1691 | 2017 |
| Adversarial autoencoders A Makhzani, J Shlens, N Jaitly, I Goodfellow, B Frey arXiv preprint arXiv:1511.05644, 2015 | 1620 | 2015 |
| Spatio-temporal correlations and visual signalling in a complete neuronal population JW Pillow, J Shlens, L Paninski, A Sher, AM Litke, EJ Chichilnisky, ... Nature 454 (7207), 995-999, 2008 | 1253 | 2008 |
| Progressive neural architecture search C Liu, B Zoph, M Neumann, J Shlens, W Hua, LJ Li, L Fei-Fei, A Yuille, ... Proceedings of the European conference on computer vision (ECCV), 19-34, 2018 | 951 | 2018 |
| Zero-shot learning by convex combination of semantic embeddings M Norouzi, T Mikolov, S Bengio, Y Singer, J Shlens, A Frome, GS Corrado, ... arXiv preprint arXiv:1312.5650, 2013 | 680 | 2013 |
| A learned representation for artistic style V Dumoulin, J Shlens, M Kudlur arXiv preprint arXiv:1610.07629, 2016 | 564 | 2016 |
| The structure of multi-neuron firing patterns in primate retina J Shlens, GD Field, JL Gauthier, MI Grivich, D Petrusca, A Sher, AM Litke, ... Journal of Neuroscience 26 (32), 8254-8266, 2006 | 510 | 2006 |
| Do better imagenet models transfer better? S Kornblith, J Shlens, QV Le Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 400 | 2019 |
| Net2net: Accelerating learning via knowledge transfer T Chen, I Goodfellow, J Shlens arXiv preprint arXiv:1511.05641, 2015 | 394 | 2015 |
| Fast, accurate detection of 100,000 object classes on a single machine T Dean, MA Ruzon, M Segal, J Shlens, S Vijayanarasimhan, J Yagnik Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 382 | 2013 |
| Functional connectivity in the retina at the resolution of photoreceptors GD Field, JL Gauthier, A Sher, M Greschner, TA Machado, LH Jepson, ... Nature 467 (7316), 673-677, 2010 | 316 | 2010 |
| Youtube-boundingboxes: A large high-precision human-annotated data set for object detection in video E Real, J Shlens, S Mazzocchi, X Pan, V Vanhoucke proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 225 | 2017 |
| Searching for efficient multi-scale architectures for dense image prediction LC Chen, MD Collins, Y Zhu, G Papandreou, B Zoph, F Schroff, H Adam, ... arXiv preprint arXiv:1809.04184, 2018 | 213 | 2018 |
| Tensorflow: large-scale machine learning on heterogeneous distributed systems (2016) M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... arXiv preprint arXiv:1603.04467 172, 2015 | 196 | 2015 |
Jeff DeanGoogle Senior Fellow & SVP, Google Research and HealthVerified email at google.com
