Jonathon Shlens - researchr alias

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Viewing Publication 1 - 42 from 42

2023

2022

Scalable Scene Flow From Point Clouds in the Real WorldPhilipp Jund, Chris Sweeney, Nichola Abdo, Zhifeng Chen, Jonathon Shlens. ral, 7(2):1589-1596, 2022. [doi]

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point CloudsZhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang 0002, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov. eccv 2022: 555-572 [doi]

Scene Transformer: A unified architecture for predicting future trajectories of multiple agentsJiquan Ngiam, Vijay Vasudevan, Benjamin Caine, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, David J. Weiss, Ben Sapp, Zhifeng Chen, Jonathon Shlens. iclr 2022: [doi]

Mitigating Bias in Calibration Error EstimationRebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer. aistats 2022: 4036-4054 [doi]

2021

Revisiting ResNets: Improved Training and Scaling StrategiesIrwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph. nips 2021: 22614-22627 [doi]

Soft Calibration Objectives for Neural NetworksArchit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs. nips 2021: 29768-29779 [doi]

Bottleneck Transformers for Visual RecognitionAravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani. cvpr 2021: 16519-16529 [doi]

Scaling Local Self-Attention for Parameter Efficient Visual BackbonesAshish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens. cvpr 2021: 12894-12904 [doi]

2020

Streaming Object Detection for 3-D Point CloudsWei Han 0002, Zhengdong Zhang, Benjamin Caine, Brandon Yang, Christoph Sprunk, Ouais Alsharif, Jiquan Ngiam, Vijay Vasudevan, Jonathon Shlens, Zhifeng Chen. eccv 2020: 423-441 [doi]

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene SegmentationLiang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, Jonathon Shlens. eccv 2020: 695-714 [doi]

Improving 3D Object Detection Through Progressive Population Based AugmentationShuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov. eccv 2020: 279-294 [doi]

Randaugment: Practical automated data augmentation with a reduced search spaceEkin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le. cvpr 2020: 3008-3017 [doi]

Revisiting Spatial Invariance with Low-Rank Local ConnectivityGamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith. icml 2020: 2868-2879 [doi]

Learning Data Augmentation Strategies for Object DetectionBarret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le. eccv 2020: 566-583 [doi]

2019

2018

Searching for Efficient Multi-Scale Architectures for Dense Image PredictionLiang-Chieh Chen, Maxwell D. Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, Jonathon Shlens. nips 2018: 8713-8724 [doi]

Progressive Neural Architecture SearchChenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan L. Yuille, Jonathan Huang, Kevin Murphy 0002. eccv 2018: 19-35 [doi]

Recurrent Segmentation for Variable Computational BudgetsLane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens. cvpr 2018: 1648-1657 [doi]

Learning a neural response metric for retinal prosthesisNishal P. Shah, Sasidhar Madugula, E. J. Chichilnisky, Yoram Singer, Jonathon Shlens. iclr 2018: [doi]

A Dataset and Architecture for Visual Reasoning with a Working MemoryGuangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo. eccv 2018: 729-745 [doi]

Learning Transferable Architectures for Scalable Image RecognitionBarret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le. cvpr 2018: 8697-8710 [doi]

2017

Pixel Recursive Super ResolutionRyan Dahl, Mohammad Norouzi, Jonathon Shlens. iccv 2017: 5449-5458 [doi]

A Learned Representation For Artistic StyleVincent Dumoulin, Jonathon Shlens, Manjunath Kudlur. iclr 2017: [doi]

Exploring the structure of a real-time, arbitrary neural artistic stylization networkGolnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens. bmvc 2017: [doi]

PixColor: Pixel Recursive ColorizationSergio Guadarrama, Ryan Dahl, David Bieber, Jonathon Shlens, Mohammad Norouzi 0002, Kevin Murphy 0002. bmvc 2017: [doi]

Conditional Image Synthesis with Auxiliary Classifier GANsAugustus Odena, Christopher Olah, Jonathon Shlens. icml 2017: 2642-2651 [doi]

YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in VideoEsteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, Vincent Vanhoucke. cvpr 2017: 7464-7473 [doi]

2016

Rethinking the Inception Architecture for Computer VisionChristian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna. cvpr 2016: 2818-2826 [doi]

2013

Fast, Accurate Detection of 100, 000 Object Classes on a Single MachineThomas L. Dean, Mark A. Ruzon, Mark Segal, Jonathon Shlens, Sudheendra Vijayanarasimhan, Jay Yagnik. cvpr 2013: 1814-1821 [doi]

DeViSE: A Deep Visual-Semantic Embedding ModelAndrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomas Mikolov. nips 2013: 2121-2129 [doi]

2012

Three Controversial Hypotheses Concerning Computation in the Primate CortexThomas L. Dean, Greg Corrado, Jonathon Shlens. AAAI 2012: 1543-1549 [doi]

Modeling the impact of common noise inputs on the network activity of retinal ganglion cellsMichael Vidne, Yashar Ahmadian, Jonathon Shlens, Jonathan W. Pillow, Jayant Kulkarni, Alan M. Litke, E. J. Chichilnisky, Eero P. Simoncelli, Liam Paninski. jcns, 33(1):97-121, 2012. [doi]

2007

Estimating Information Rates with Confidence Intervals in Neural Spike TrainsJonathon Shlens, Matthew B. Kennel, Henry D. I. Abarbanel, E. J. Chichilnisky. neco, 19(7):1683-1719, 2007. [doi]

2005

Estimating Entropy Rates with Bayesian Confidence IntervalsMatthew B. Kennel, Jonathon Shlens, Henry D. I. Abarbanel, E. J. Chichilnisky. neco, 17(7):1531-1576, 2005. [doi]

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2005

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