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Semantic ScholarJonathon Shlens
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2010 – today
- 2018
[c14]Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens:
Recurrent Segmentation for Variable Computational Budgets. CVPR Workshops 2018: 1648-1657- [c13]Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le:
Learning Transferable Architectures for Scalable Image Recognition. CVPR 2018: 8697-8710 - [c12]Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan L. Yuille, Jonathan Huang, Kevin Murphy:
Progressive Neural Architecture Search. ECCV (1) 2018: 19-35 - [c11]Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo:
A Dataset and Architecture for Visual Reasoning with a Working Memory. ECCV (10) 2018: 729-745 - [c10]Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, Jonathon Shlens:
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction. NeurIPS 2018: 8713-8724 - [i25]Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo:
A dataset and architecture for visual reasoning with a working memory. CoRR abs/1803.06092 (2018) - [i24]Simon Kornblith, Jonathon Shlens, Quoc V. Le:
Do Better ImageNet Models Transfer Better? CoRR abs/1805.08974 (2018) - [i23]Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, Jonathon Shlens:
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction. CoRR abs/1809.04184 (2018) - 2017
- [c9]Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens:
Exploring the structure of a real-time, arbitrary neural artistic stylization network. BMVC 2017 - [c8]Sergio Guadarrama, Ryan Dahl, David Bieber, Jonathon Shlens, Mohammad Norouzi, Kevin Murphy:
PixColor: Pixel Recursive Colorization. BMVC 2017 - [c7]Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, Vincent Vanhoucke:
YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video. CVPR 2017: 7464-7473 - [c6]Ryan Dahl, Mohammad Norouzi, Jonathon Shlens:
Pixel Recursive Super Resolution. ICCV 2017: 5449-5458 - [c5]Augustus Odena, Christopher Olah, Jonathon Shlens:
Conditional Image Synthesis with Auxiliary Classifier GANs. ICML 2017: 2642-2651 - [i22]Ryan Dahl, Mohammad Norouzi, Jonathon Shlens:
Pixel Recursive Super Resolution. CoRR abs/1702.00783 (2017) - [i21]Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, Vincent Vanhoucke:
YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video. CoRR abs/1702.00824 (2017) - [i20]Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens:
Exploring the structure of a real-time, arbitrary neural artistic stylization network. CoRR abs/1705.06830 (2017) - [i19]Sergio Guadarrama, Ryan Dahl, David Bieber, Mohammad Norouzi, Jonathon Shlens, Kevin Murphy:
PixColor: Pixel Recursive Colorization. CoRR abs/1705.07208 (2017) - [i18]Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le:
Learning Transferable Architectures for Scalable Image Recognition. CoRR abs/1707.07012 (2017) - [i17]Lane McIntosh, David Sussillo, Niru Maheswaranathan, Jonathon Shlens:
Recurrent Segmentation for Variable Computational Budgets. CoRR abs/1711.10151 (2017) - [i16]Chenxi Liu, Barret Zoph, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan L. Yuille, Jonathan Huang, Kevin Murphy:
Progressive Neural Architecture Search. CoRR abs/1712.00559 (2017) - 2016
- [c4]Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna:
Rethinking the Inception Architecture for Computer Vision. CVPR 2016: 2818-2826 - [i15]Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng:
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. CoRR abs/1603.04467 (2016) - [i14]Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur:
A Learned Representation For Artistic Style. CoRR abs/1610.07629 (2016) - [i13]Augustus Odena, Christopher Olah, Jonathon Shlens:
Conditional Image Synthesis With Auxiliary Classifier GANs. CoRR abs/1610.09585 (2016) - 2015
- [i12]Tianqi Chen, Ian J. Goodfellow, Jonathon Shlens:
Net2Net: Accelerating Learning via Knowledge Transfer. CoRR abs/1511.05641 (2015) - [i11]Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian J. Goodfellow:
Adversarial Autoencoders. CoRR abs/1511.05644 (2015) - [i10]Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna:
Rethinking the Inception Architecture for Computer Vision. CoRR abs/1512.00567 (2015) - 2014
- [i9]
- [i8]
- [i7]
- [i6]
- [i5]
- [i4]Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy:
Explaining and Harnessing Adversarial Examples. CoRR abs/1412.6572 (2014) - [i3]Sudheendra Vijayanarasimhan, Jonathon Shlens, Rajat Monga, Jay Yagnik:
Deep Networks With Large Output Spaces. CoRR abs/1412.7479 (2014) - 2013
- [c3]Thomas L. Dean, Mark A. Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan, Jay Yagnik:
Fast, Accurate Detection of 100, 000 Object Classes on a Single Machine. CVPR 2013: 1814-1821 - [c2]Andrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomas Mikolov:
DeViSE: A Deep Visual-Semantic Embedding Model. NIPS 2013: 2121-2129 - [i2]Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean:
Zero-Shot Learning by Convex Combination of Semantic Embeddings. CoRR abs/1312.5650 (2013) - [i1]Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer:
Using Web Co-occurrence Statistics for Improving Image Categorization. CoRR abs/1312.5697 (2013) - 2012
- [j3]Michael Vidne, Yashar Ahmadian, Jonathon Shlens, Jonathan W. Pillow, Jayant Kulkarni, Alan M. Litke, E. J. Chichilnisky, Eero P. Simoncelli, Liam Paninski:
Modeling the impact of common noise inputs on the network activity of retinal ganglion cells. Journal of Computational Neuroscience 33(1): 97-121 (2012) - [c1]Thomas L. Dean, Greg Corrado, Jonathon Shlens:
Three Controversial Hypotheses Concerning Computation in the Primate Cortex. AAAI 2012
2000 – 2009
- 2007
- [j2]Jonathon Shlens, Matthew B. Kennel, Henry D. I. Abarbanel, E. J. Chichilnisky:
Estimating Information Rates with Confidence Intervals in Neural Spike Trains. Neural Computation 19(7): 1683-1719 (2007) - 2005
- [j1]Matthew B. Kennel, Jonathon Shlens, Henry D. I. Abarbanel, E. J. Chichilnisky:
Estimating Entropy Rates with Bayesian Confidence Intervals. Neural Computation 17(7): 1531-1576 (2005)
Coauthor Index
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