Estimating Entropy Rates with Bayesian Confidence Intervals. - Matthew B. Kennel; Jonathon Shlens; Henry D. I. Abarbanel; E. J. Chichilnisky (Neural Comput., 2005)

Estimating Information Rates with Confidence Intervals in Neural Spike Trains. - Jonathon Shlens; Matthew B. Kennel; Henry D. I. Abarbanel; E. J. Chichilnisky (Neural Comput., 2007)

Three Controversial Hypotheses Concerning Computation in the Primate Cortex. - Thomas L. Dean; Greg Corrado; Jonathon Shlens (AAAI, 2012)

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells. - Michael Vidne; Yashar Ahmadian; Jonathon Shlens; Jonathan W. Pillow; Jayant Kulkarni; Alan M. Litke; E. J. Chichilnisky; Eero P. Simoncelli; Liam Paninski (J. Comput. Neurosci., 2012)

Fast, Accurate Detection of 100, 000 Object Classes on a Single Machine. - Thomas L. Dean; Mark A. Ruzon; Mark Segal; Jonathon Shlens; Sudheendra Vijayanarasimhan; Jay Yagnik (CVPR, 2013)

DeViSE: A Deep Visual-Semantic Embedding Model. - Andrea Frome; Gregory S. Corrado; Jonathon Shlens; Samy Bengio; Jeffrey Dean; Marc'Aurelio Ranzato; Tomás Mikolov (NIPS, 2013)

Using Web Co-occurrence Statistics for Improving Image Categorization. - Samy Bengio; Jeffrey Dean; Dumitru Erhan; Eugene Ie; Quoc V. Le; Andrew Rabinovich; Jonathon Shlens; Yoram Singer (CoRR, 2013)

Zero-Shot Learning by Convex Combination of Semantic Embeddings. - Mohammad Norouzi 002; Tomás Mikolov; Samy Bengio; Yoram Singer; Jonathon Shlens; Andrea Frome; Greg Corrado; Jeffrey Dean (ICLR, 2014)

A Tutorial on Principal Component Analysis. - Jonathon Shlens (CoRR, 2014)

A Light Discussion and Derivation of Entropy. - Jonathon Shlens (CoRR, 2014)

Notes on Generalized Linear Models of Neurons. - Jonathon Shlens (CoRR, 2014)

Notes on Kullback-Leibler Divergence and Likelihood. - Jonathon Shlens (CoRR, 2014)

A Tutorial on Independent Component Analysis. - Jonathon Shlens (CoRR, 2014)

Explaining and Harnessing Adversarial Examples. - Ian J. Goodfellow; Jonathon Shlens; Christian Szegedy (ICLR (Poster), 2015)

Adversarial Autoencoders. - Alireza Makhzani; Jonathon Shlens; Navdeep Jaitly; Ian J. Goodfellow (CoRR, 2015)

Deep Networks With Large Output Spaces. - Sudheendra Vijayanarasimhan; Jonathon Shlens; Rajat Monga; Jay Yagnik (ICLR (Workshop), 2015)

Rethinking the Inception Architecture for Computer Vision. - Christian Szegedy; Vincent Vanhoucke; Sergey Ioffe; Jonathon Shlens; Zbigniew Wojna (CVPR, 2016)

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. - Martín Abadi; Ashish Agarwal; Paul Barham 001; Eugene Brevdo; Zhifeng Chen; Craig Citro; Gregory S. Corrado; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Ian J. Goodfellow; et al. (CoRR, 2016)

Net2Net: Accelerating Learning via Knowledge Transfer. - Tianqi Chen; Ian J. Goodfellow; Jonathon Shlens (ICLR, 2016)

Exploring the structure of a real-time, arbitrary neural artistic stylization network. - Golnaz Ghiasi; Honglak Lee; Manjunath Kudlur; Vincent Dumoulin; Jonathon Shlens (BMVC, 2017)

PixColor: Pixel Recursive Colorization. - Sergio Guadarrama; Ryan Dahl; David Bieber; Jonathon Shlens; Mohammad Norouzi 002; Kevin Murphy 002 (BMVC, 2017)

YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video. - Esteban Real; Jonathon Shlens; Stefano Mazzocchi; Xin Pan; Vincent Vanhoucke (CVPR, 2017)

Pixel Recursive Super Resolution. - Ryan Dahl; Mohammad Norouzi 002; Jonathon Shlens (ICCV, 2017)

A Learned Representation For Artistic Style. - Vincent Dumoulin; Jonathon Shlens; Manjunath Kudlur (ICLR (Poster), 2017)

Conditional Image Synthesis with Auxiliary Classifier GANs. - Augustus Odena; Christopher Olah; Jonathon Shlens (ICML, 2017)

Progressive Neural Architecture Search. - Chenxi Liu 001; Barret Zoph; Jonathon Shlens; Wei Hua; Li-Jia Li 001; Li Fei-Fei 001; Alan L. Yuille; Jonathan Huang; Kevin Murphy 002 (CoRR, 2017)

Recurrent Segmentation for Variable Computational Budgets. - Lane McIntosh; Niru Maheswaranathan; David Sussillo; Jonathon Shlens (CVPR Workshops, 2018)

Learning Transferable Architectures for Scalable Image Recognition. - Barret Zoph; Vijay Vasudevan; Jonathon Shlens; Quoc V. Le (CVPR, 2018)

Progressive Neural Architecture Search. - Chenxi Liu 001; Barret Zoph; Maxim Neumann; Jonathon Shlens; Wei Hua; Li-Jia Li 001; Li Fei-Fei 001; Alan L. Yuille; Jonathan Huang; Kevin Murphy 002 (ECCV (1), 2018)

A Dataset and Architecture for Visual Reasoning with a Working Memory. - Guangyu Robert Yang; Igor Ganichev; Xiao-Jing Wang; Jonathon Shlens; David Sussillo (ECCV (10), 2018)

Learning a neural response metric for retinal prosthesis. - Nishal P. Shah; Sasidhar Madugula; E. J. Chichilnisky; Yoram Singer; Jonathon Shlens (ICLR (Poster), 2018)

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction. - Liang-Chieh Chen; Maxwell D. Collins; Yukun Zhu; George Papandreou; Barret Zoph; Florian Schroff; Hartwig Adam; Jonathon Shlens (NeurIPS, 2018)

Do Better ImageNet Models Transfer Better? - Simon Kornblith; Jonathon Shlens; Quoc V. Le (CVPR, 2019)

Attention Augmented Convolutional Networks. - Irwan Bello; Barret Zoph; Quoc Le 001; Ashish Vaswani; Jonathon Shlens (ICCV, 2019)

A Learned Representation for Scalable Vector Graphics. - Raphael Gontijo Lopes; David Ha; Douglas Eck; Jonathon Shlens (DGS@ICLR, 2019)

Stand-Alone Self-Attention in Vision Models. - Niki Parmar; Prajit Ramachandran; Ashish Vaswani; Irwan Bello; Anselm Levskaya; Jonathon Shlens (NeurIPS, 2019)

A Fourier Perspective on Model Robustness in Computer Vision. - Dong Yin; Raphael Gontijo Lopes; Jonathon Shlens; Ekin Dogus Cubuk; Justin Gilmer (NeurIPS, 2019)

Accelerating Training of Deep Neural Networks with a Standardization Loss. - Jasmine Collins; Johannes Ballé; Jonathon Shlens (CoRR, 2019)

Using Videos to Evaluate Image Model Robustness. - Keren Gu; Brandon Yang; Jiquan Ngiam; Quoc V. Le; Jonathon Shlens (CoRR, 2019)

Using learned optimizers to make models robust to input noise. - Luke Metz; Niru Maheswaranathan; Jonathon Shlens; Jascha Sohl-Dickstein; Ekin D. Cubuk (CoRR, 2019)

Visual Wake Words Dataset. - Aakanksha Chowdhery; Pete Warden; Jonathon Shlens; Andrew Howard 002; Rocky Rhodes (CoRR, 2019)

StarNet: Targeted Computation for Object Detection in Point Clouds. - Jiquan Ngiam; Benjamin Caine; Wei Han 002; Brandon Yang; Yuning Chai; Pei Sun; Yin Zhou; Xi Yi; Ouais Alsharif; Patrick Nguyen; Zhifeng Chen; Jonathon Shlens; et al. (CoRR, 2019)

RandAugment: Practical data augmentation with no separate search. - Ekin D. Cubuk; Barret Zoph; Jonathon Shlens; Quoc V. Le (CoRR, 2019)

Scalability in Perception for Autonomous Driving: Waymo Open Dataset. - Pei Sun; Henrik Kretzschmar; Xerxes Dotiwalla; Aurelien Chouard; Vijaysai Patnaik; Paul Tsui; James Guo; Yin Zhou; Yuning Chai; Benjamin Caine; Vijay Vasudevan; Wei Han 002; et al. (CVPR, 2020)

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. - Liang-Chieh Chen; Raphael Gontijo Lopes; Bowen Cheng; Maxwell D. Collins; Ekin D. Cubuk; Barret Zoph; Hartwig Adam; Jonathon Shlens (ECCV (9), 2020)

Improving 3D Object Detection Through Progressive Population Based Augmentation. - Shuyang 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; et al. (ECCV (21), 2020)

Streaming Object Detection for 3-D Point Clouds. - Wei Han 002; Zhengdong Zhang; Benjamin Caine; Brandon Yang; Christoph Sprunk; Ouais Alsharif; Jiquan Ngiam; Vijay Vasudevan; Jonathon Shlens; Zhifeng Chen (ECCV (18), 2020)

Learning Data Augmentation Strategies for Object Detection. - Barret Zoph; Ekin D. Cubuk; Golnaz Ghiasi; Tsung-Yi Lin; Jonathon Shlens; Quoc V. Le (ECCV (27), 2020)

Revisiting Spatial Invariance with Low-Rank Local Connectivity. - Gamaleldin F. Elsayed; Prajit Ramachandran; Jonathon Shlens; Simon Kornblith (ICML, 2020)

RandAugment: Practical Automated Data Augmentation with a Reduced Search Space. - Ekin Dogus Cubuk; Barret Zoph; Jonathon Shlens; Quoc Le 001 (NeurIPS, 2020)

Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. - Liang-Chieh Chen; Raphael Gontijo Lopes; Bowen Cheng; Maxwell D. Collins; Ekin D. Cubuk; Barret Zoph; Hartwig Adam; Jonathon Shlens (CoRR, 2020)

Bottleneck Transformers for Visual Recognition. - Aravind Srinivas; Tsung-Yi Lin; Niki Parmar; Jonathon Shlens; Pieter Abbeel; Ashish Vaswani (CVPR, 2021)

Scaling Local Self-Attention for Parameter Efficient Visual Backbones. - Ashish Vaswani; Prajit Ramachandran; Aravind Srinivas; Niki Parmar; Blake A. Hechtman; Jonathon Shlens (CVPR, 2021)

Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. - Scott Ettinger; Shuyang Cheng; Benjamin Caine; Chenxi Liu 001; Hang Zhao; Sabeek Pradhan; Yuning Chai; Ben Sapp; Charles R. Qi; Yin Zhou; Zoey Yang; Aurelien Chouard; et al. (ICCV, 2021)

Revisiting ResNets: Improved Training and Scaling Strategies. - Irwan Bello; William Fedus; Xianzhi Du; Ekin Dogus Cubuk; Aravind Srinivas; Tsung-Yi Lin; Jonathon Shlens; Barret Zoph (NeurIPS, 2021)

Soft Calibration Objectives for Neural Networks. - Archit Karandikar; Nicholas Cain; Dustin Tran; Balaji Lakshminarayanan; Jonathon Shlens; Michael C. Mozer; Becca Roelofs (NeurIPS, 2021)

Pseudo-labeling for Scalable 3D Object Detection. - Benjamin Caine; Rebecca Roelofs; Vijay Vasudevan; Jiquan Ngiam; Yuning Chai; Zhifeng Chen; Jonathon Shlens (CoRR, 2021)

Scene Transformer: A unified multi-task model for behavior prediction and planning. - Jiquan Ngiam; Benjamin Caine; Vijay Vasudevan; Zhengdong Zhang; Hao-Tien Lewis Chiang; Jeffrey Ling; Rebecca Roelofs; Alex Bewley; Chenxi Liu 001; Ashish Venugopal; David Weiss 001; Benjamin Sapp; et al. (CoRR, 2021)

Mitigating Bias in Calibration Error Estimation. - Rebecca Roelofs; Nicholas Cain; Jonathon Shlens; Michael C. Mozer (AISTATS, 2022)

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. - Zhaoqi Leng; Shuyang Cheng; Benjamin Caine; Weiyue Wang 002; Xiao Zhang; Jonathon Shlens; Mingxing Tan; Dragomir Anguelov (ECCV (31), 2022)

Scene Transformer: A unified architecture for predicting future trajectories of multiple agents. - Jiquan Ngiam; Vijay Vasudevan; Benjamin Caine; Zhengdong Zhang; Hao-Tien Lewis Chiang; Jeffrey Ling; Rebecca Roelofs; Alex Bewley; Chenxi Liu 001; Ashish Venugopal; David J. Weiss; Ben Sapp; et al. (ICLR, 2022)

Perceptual Grouping in Vision-Language Models. - Kanchana Ranasinghe; Brandon McKinzie; Sachin Ravi; Yinfei Yang; Alexander Toshev; Jonathon Shlens (CoRR, 2022)

Scalable Scene Flow From Point Clouds in the Real World. - Philipp Jund; Chris Sweeney; Nichola Abdo; Zhifeng Chen; Jonathon Shlens (IEEE Robotics Autom. Lett., 2022)

STAIR: Learning Sparse Text and Image Representation in Grounded Tokens. - Chen Chen 005; Bowen Zhang 002; Liangliang Cao; Jiguang Shen; Tom Gunter; Albin Madappally Jose; Alexander Toshev; Yantao Zheng; Jonathon Shlens; Ruoming Pang; Yinfei Yang (EMNLP, 2023)

Perceptual Grouping in Contrastive Vision-Language Models. - Kanchana Ranasinghe; Brandon McKinzie; Sachin Ravi; Yinfei Yang; Alexander Toshev; Jonathon Shlens (ICCV, 2023)

Robustness in Multimodal Learning under Train-Test Modality Mismatch. - Brandon McKinzie; Vaishaal Shankar; Joseph Yitan Cheng; Yinfei Yang; Jonathon Shlens; Alexander T. Toshev (ICML, 2023)

STAIR: Learning Sparse Text and Image Representation in Grounded Tokens. - Chen Chen 005; Bowen Zhang 002; Liangliang Cao; Jiguang Shen; Tom Gunter; Albin Madappally Jose; Alexander Toshev; Jonathon Shlens; Ruoming Pang; Yinfei Yang (CoRR, 2023)

On Robustness in Multimodal Learning. - Brandon McKinzie; Joseph Yitan Cheng; Vaishaal Shankar; Yinfei Yang; Jonathon Shlens; Alexander Toshev (CoRR, 2023)

MOFI: Learning Image Representations from Noisy Entity Annotated Images. - Wentao Wu; Aleksei Timofeev; Chen Chen 005; Bowen Zhang 002; Kun Duan; Shuangning Liu; Yantao Zheng; Jonathon Shlens; Xianzhi Du; Zhe Gan; Yinfei Yang (CoRR, 2023)

MOFI: Learning Image Representations from Noisy Entity Annotated Images. - Wentao Wu; Aleksei Timofeev; Chen Chen 005; Bowen Zhang 002; Kun Duan; Shuangning Liu; Yantao Zheng; Jonathon Shlens; Xianzhi Du; Yinfei Yang (ICLR, 2024)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)

Towards flexible perception with visual memory. - Robert Geirhos; Priyank Jaini; Austin Stone; Sourabh Medapati; Xi Yi; George Toderici; Abhijit Ogale; Jonathon Shlens (CoRR, 2024)

Learning Visual Composition through Improved Semantic Guidance. - Austin Stone; Hagen Soltau; Robert Geirhos; Xi Yi; Ye Xia; Bingyi Cao; Kaifeng Chen; Abhijit Ogale; Jonathon Shlens (CVPR, 2025)

MedGemma Technical Report. - Andrew Sellergren; Sahar Kazemzadeh; Tiam Jaroensri; Atilla P. Kiraly; Madeleine Traverse; Timo Kohlberger; Shawn Xu; Fayaz Jamil; Cían Hughes; Charles Lau; Justin Chen; Fereshteh Mahvar; et al. (CoRR, 2025)