Jonathon Shlens

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 82

Top Topics

Object Detection

Vector Graphics

Top Venues

Publications

Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan
Capabilities of Gemini Models in Medicine. CoRR (2024)
Wentao Wu, Aleksei Timofeev, Chen Chen, Bowen Zhang, Kun Duan, Shuangning Liu, Yantao Zheng, Jonathon Shlens, Xianzhi Du, Yinfei Yang
MOFI: Learning Image Representations from Noisy Entity Annotated Images. ICLR (2024)
Wentao Wu, Aleksei Timofeev, Chen Chen, Bowen Zhang, Kun Duan, Shuangning Liu, Yantao Zheng, Jonathon Shlens, Xianzhi Du, Zhe Gan, Yinfei Yang
MOFI: Learning Image Representations from Noisy Entity Annotated Images. CoRR (2023)
Chen Chen, Bowen Zhang, Liangliang Cao, Jiguang Shen, Tom Gunter, Albin Madappally Jose, Alexander Toshev, Yantao Zheng, Jonathon Shlens, Ruoming Pang, Yinfei Yang
STAIR: Learning Sparse Text and Image Representation in Grounded Tokens. EMNLP (2023)
Kanchana Ranasinghe, Brandon McKinzie, Sachin Ravi, Yinfei Yang, Alexander Toshev, Jonathon Shlens
Perceptual Grouping in Contrastive Vision-Language Models. ICCV (2023)
Brandon McKinzie, Vaishaal Shankar, Joseph Yitan Cheng, Yinfei Yang, Jonathon Shlens, Alexander T. Toshev
Robustness in Multimodal Learning under Train-Test Modality Mismatch. ICML (2023)
Brandon McKinzie, Joseph Cheng, Vaishaal Shankar, Yinfei Yang, Jonathon Shlens, Alexander Toshev
On Robustness in Multimodal Learning. CoRR (2023)
Chen Chen, Bowen Zhang, Liangliang Cao, Jiguang Shen, Tom Gunter, Albin Madappally Jose, Alexander Toshev, Jonathon Shlens, Ruoming Pang, Yinfei Yang
STAIR: Learning Sparse Text and Image Representation in Grounded Tokens. CoRR (2023)
Jiquan 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
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents. ICLR (2022)
Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. ECCV (31) (2022)
Kanchana Ranasinghe, Brandon McKinzie, Sachin Ravi, Yinfei Yang, Alexander Toshev, Jonathon Shlens
Perceptual Grouping in Vision-Language Models. CoRR (2022)
Philipp Jund, Chris Sweeney, Nichola Abdo, Zhifeng Chen, Jonathon Shlens
Scalable Scene Flow From Point Clouds in the Real World. IEEE Robotics Autom. Lett. 7 (2) (2022)
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer
Mitigating Bias in Calibration Error Estimation. AISTATS (2022)
Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. CoRR (2022)
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs
Soft Calibration Objectives for Neural Networks. CoRR (2021)
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani
Bottleneck Transformers for Visual Recognition. CVPR (2021)
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens
Scaling Local Self-Attention for Parameter Efficient Visual Backbones. CVPR (2021)
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Benjamin Sapp, Charles R. Qi, Yin Zhou, Zoey Yang, Aurelien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, Dragomir Anguelov
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. CoRR (2021)
Benjamin Caine, Rebecca Roelofs, Vijay Vasudevan, Jiquan Ngiam, Yuning Chai, Zhifeng Chen, Jonathon Shlens
Pseudo-labeling for Scalable 3D Object Detection. CoRR (2021)
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani
Bottleneck Transformers for Visual Recognition. CoRR (2021)
Jiquan Ngiam, Benjamin Caine, Vijay Vasudevan, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, David Weiss, Benjamin Sapp, Zhifeng Chen, Jonathon Shlens
Scene Transformer: A unified multi-task model for behavior prediction and planning. CoRR (2021)
Irwan Bello, William Fedus, Xianzhi Du, Ekin D. Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph
Revisiting ResNets: Improved Training and Scaling Strategies. CoRR (2021)
Philipp Jund, Chris Sweeney, Nichola Abdo, Zhifeng Chen, Jonathon Shlens
Scalable Scene Flow from Point Clouds in the Real World. CoRR (2021)
Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph
Revisiting ResNets: Improved Training and Scaling Strategies. NeurIPS (2021)
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R. Qi, Yin Zhou, Zoey Yang, Aurelien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, Dragomir Anguelov
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. ICCV (2021)
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs
Soft Calibration Objectives for Neural Networks. NeurIPS (2021)
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake A. Hechtman, Jonathon Shlens
Scaling Local Self-Attention for Parameter Efficient Visual Backbones. CoRR (2021)
Wei Han, Zhengdong Zhang, Benjamin Caine, Brandon Yang, Christoph Sprunk, Ouais Alsharif, Jiquan Ngiam, Vijay Vasudevan, Jonathon Shlens, Zhifeng Chen
Streaming Object Detection for 3-D Point Clouds. CoRR (2020)
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov
Scalability in Perception for Autonomous Driving: Waymo Open Dataset. CVPR (2020)
Wei Han, Zhengdong Zhang, Benjamin Caine, Brandon Yang, Christoph Sprunk, Ouais Alsharif, Jiquan Ngiam, Vijay Vasudevan, Jonathon Shlens, Zhifeng Chen
Streaming Object Detection for 3-D Point Clouds. ECCV (18) (2020)
Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, Jonathon Shlens
Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. CoRR (2020)
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, Dragomir Anguelov
Improving 3D Object Detection Through Progressive Population Based Augmentation. ECCV (21) (2020)
Gamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith
Revisiting Spatial Invariance with Low-Rank Local Connectivity. CoRR (2020)
Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le
Randaugment: Practical automated data augmentation with a reduced search space. CVPR Workshops (2020)
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer
Mitigating bias in calibration error estimation. CoRR (2020)
Gamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith
Revisiting Spatial Invariance with Low-Rank Local Connectivity. ICML (2020)
Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, Jonathon Shlens
Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. ECCV (9) (2020)
Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le
Learning Data Augmentation Strategies for Object Detection. ECCV (27) (2020)
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, Dragomir Anguelov
Improving 3D Object Detection through Progressive Population Based Augmentation. CoRR (2020)
Irwan Bello, Barret Zoph, Quoc Le, Ashish Vaswani, Jonathon Shlens
Attention Augmented Convolutional Networks. ICCV (2019)
Jasmine Collins, Johannes Ballé, Jonathon Shlens
Accelerating Training of Deep Neural Networks with a Standardization Loss. CoRR (2019)
Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens
A Learned Representation for Scalable Vector Graphics. CoRR (2019)
Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens
A Learned Representation for Scalable Vector Graphics. ICCV (2019)
Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le
RandAugment: Practical data augmentation with no separate search. CoRR (2019)
Irwan Bello, Barret Zoph, Ashish Vaswani, Jonathon Shlens, Quoc V. Le
Attention Augmented Convolutional Networks. CoRR (2019)
Simon Kornblith, Jonathon Shlens, Quoc V. Le
Do Better ImageNet Models Transfer Better? CVPR (2019)
Luke Metz, Niru Maheswaranathan, Jonathon Shlens, Jascha Sohl-Dickstein, Ekin D. Cubuk
Using learned optimizers to make models robust to input noise. CoRR (2019)
Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens
A Learned Representation for Scalable Vector Graphics. DGS@ICLR (2019)
Aakanksha Chowdhery, Pete Warden, Jonathon Shlens, Andrew Howard, Rocky Rhodes
Visual Wake Words Dataset. CoRR (2019)
Keren Gu, Brandon Yang, Jiquan Ngiam, Quoc V. Le, Jonathon Shlens
Using Videos to Evaluate Image Model Robustness. CoRR (2019)
Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le
Learning Data Augmentation Strategies for Object Detection. CoRR (2019)
Dong Yin, Raphael Gontijo Lopes, Jonathon Shlens, Ekin D. Cubuk, Justin Gilmer
A Fourier Perspective on Model Robustness in Computer Vision. CoRR (2019)
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, Jonathon Shlens
Stand-Alone Self-Attention in Vision Models. CoRR (2019)
Jiquan Ngiam, Benjamin Caine, Wei Han, Brandon Yang, Yuning Chai, Pei Sun, Yin Zhou, Xi Yi, Ouais Alsharif, Patrick Nguyen, Zhifeng Chen, Jonathon Shlens, Vijay Vasudevan
StarNet: Targeted Computation for Object Detection in Point Clouds. CoRR (2019)
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov
Scalability in Perception for Autonomous Driving: Waymo Open Dataset. CoRR (2019)
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le
Learning Transferable Architectures for Scalable Image Recognition. CVPR (2018)
Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo
A dataset and architecture for visual reasoning with a working memory. CoRR (2018)
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)
Nishal P. Shah, Sasidhar Madugula, E. J. Chichilnisky, Yoram Singer, Jonathon Shlens
Learning a neural response metric for retinal prosthesis. ICLR (Poster) (2018)
Simon Kornblith, Jonathon Shlens, Quoc V. Le
Do Better ImageNet Models Transfer Better? CoRR (2018)
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)
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 (2018)
Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens
Recurrent Segmentation for Variable Computational Budgets. CVPR Workshops (2018)
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)
Lane McIntosh, David Sussillo, Niru Maheswaranathan, Jonathon Shlens
Recurrent Segmentation for Variable Computational Budgets. CoRR (2017)
Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur
A Learned Representation For Artistic Style. ICLR (Poster) (2017)
Sergio Guadarrama, Ryan Dahl, David Bieber, Jonathon Shlens, Mohammad Norouzi, Kevin Murphy
PixColor: Pixel Recursive Colorization. BMVC (2017)
Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens
Exploring the structure of a real-time, arbitrary neural artistic stylization network. BMVC (2017)
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)
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 (2017)
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 (2017)
Ryan Dahl, Mohammad Norouzi, Jonathon Shlens
Pixel Recursive Super Resolution. ICCV (2017)
Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens
Exploring the structure of a real-time, arbitrary neural artistic stylization network. CoRR (2017)
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le
Learning Transferable Architectures for Scalable Image Recognition. CoRR (2017)
Sergio Guadarrama, Ryan Dahl, David Bieber, Mohammad Norouzi, Jonathon Shlens, Kevin Murphy
PixColor: Pixel Recursive Colorization. CoRR (2017)
Ryan Dahl, Mohammad Norouzi, Jonathon Shlens
Pixel Recursive Super Resolution. CoRR (2017)
Augustus Odena, Christopher Olah, Jonathon Shlens
Conditional Image Synthesis with Auxiliary Classifier GANs. ICML (2017)
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 (2016)
Tianqi Chen, Ian J. Goodfellow, Jonathon Shlens
Net2Net: Accelerating Learning via Knowledge Transfer. ICLR (2016)
Augustus Odena, Christopher Olah, Jonathon Shlens
Conditional Image Synthesis With Auxiliary Classifier GANs. CoRR (2016)
Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur
A Learned Representation For Artistic Style. CoRR (2016)
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna
Rethinking the Inception Architecture for Computer Vision. CVPR (2016)
Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy
Explaining and Harnessing Adversarial Examples. ICLR (Poster) (2015)
Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian J. Goodfellow
Adversarial Autoencoders. CoRR (2015)
Sudheendra Vijayanarasimhan, Jonathon Shlens, Rajat Monga, Jay Yagnik
Deep Networks With Large Output Spaces. ICLR (Workshop) (2015)
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna
Rethinking the Inception Architecture for Computer Vision. CoRR (2015)
Jonathon Shlens
A Tutorial on Independent Component Analysis. CoRR (2014)
Jonathon Shlens
Notes on Kullback-Leibler Divergence and Likelihood. CoRR (2014)
Jonathon Shlens
A Light Discussion and Derivation of Entropy. CoRR (2014)
Jonathon Shlens
Notes on Generalized Linear Models of Neurons. CoRR (2014)
Mohammad Norouzi, Tomás Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean
Zero-Shot Learning by Convex Combination of Semantic Embeddings. ICLR (2014)
Jonathon Shlens
A Tutorial on Principal Component Analysis. CoRR (2014)
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 (2013)
Andrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomás Mikolov
DeViSE: A Deep Visual-Semantic Embedding Model. NIPS (2013)
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)
Thomas L. Dean, Greg Corrado, Jonathon Shlens
Three Controversial Hypotheses Concerning Computation in the Primate Cortex. AAAI (2012)
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. J. Comput. Neurosci. 33 (1) (2012)
Jonathon Shlens, Matthew B. Kennel, Henry D. I. Abarbanel, E. J. Chichilnisky
Estimating Information Rates with Confidence Intervals in Neural Spike Trains. Neural Comput. 19 (7) (2007)
Matthew B. Kennel, Jonathon Shlens, Henry D. I. Abarbanel, E. J. Chichilnisky
Estimating Entropy Rates with Bayesian Confidence Intervals. Neural Comput. 17 (7) (2005)