Jonathon Shlens

According to our database1, Jonathon Shlens authored at least 50 papers between 2005 and 2020.

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Bibliography

2020
Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.
CoRR, 2020

Streaming Object Detection for 3-D Point Clouds.
CoRR, 2020

Improving 3D Object Detection through Progressive Population Based Augmentation.
CoRR, 2020

Revisiting Spatial Invariance with Low-Rank Local Connectivity.
CoRR, 2020

2019
Scalability in Perception for Autonomous Driving: Waymo Open Dataset.
CoRR, 2019

RandAugment: Practical data augmentation with no separate search.
CoRR, 2019

StarNet: Targeted Computation for Object Detection in Point Clouds.
CoRR, 2019

Learning Data Augmentation Strategies for Object Detection.
CoRR, 2019

Visual Wake Words Dataset.
CoRR, 2019

Using learned optimizers to make models robust to input noise.
CoRR, 2019

Using Videos to Evaluate Image Model Robustness.
CoRR, 2019

Attention Augmented Convolutional Networks.
CoRR, 2019

Accelerating Training of Deep Neural Networks with a Standardization Loss.
CoRR, 2019

A Fourier Perspective on Model Robustness in Computer Vision.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stand-Alone Self-Attention in Vision Models.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Learned Representation for Scalable Vector Graphics.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Attention Augmented Convolutional Networks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Do Better ImageNet Models Transfer Better?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning a neural response metric for retinal prosthesis.
Proceedings of the 6th International Conference on Learning Representations, 2018

A Dataset and Architecture for Visual Reasoning with a Working Memory.
Proceedings of the Computer Vision - ECCV 2018, 2018

Progressive Neural Architecture Search.
Proceedings of the Computer Vision - ECCV 2018, 2018

Learning Transferable Architectures for Scalable Image Recognition.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Recurrent Segmentation for Variable Computational Budgets.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017
Progressive Neural Architecture Search.
CoRR, 2017

Conditional Image Synthesis with Auxiliary Classifier GANs.
Proceedings of the 34th International Conference on Machine Learning, 2017

A Learned Representation For Artistic Style.
Proceedings of the 5th International Conference on Learning Representations, 2017

Pixel Recursive Super Resolution.
Proceedings of the IEEE International Conference on Computer Vision, 2017

YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

PixColor: Pixel Recursive Colorization.
Proceedings of the British Machine Vision Conference 2017, 2017

Exploring the structure of a real-time, arbitrary neural artistic stylization network.
Proceedings of the British Machine Vision Conference 2017, 2017

2016
Net2Net: Accelerating Learning via Knowledge Transfer.
Proceedings of the 4th International Conference on Learning Representations, 2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.
CoRR, 2016

Rethinking the Inception Architecture for Computer Vision.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Deep Networks With Large Output Spaces.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Adversarial Autoencoders.
CoRR, 2015

Explaining and Harnessing Adversarial Examples.
Proceedings of the 3rd International Conference on Learning Representations, 2015

2014
A Tutorial on Independent Component Analysis.
CoRR, 2014

Notes on Kullback-Leibler Divergence and Likelihood.
CoRR, 2014

Notes on Generalized Linear Models of Neurons.
CoRR, 2014

A Light Discussion and Derivation of Entropy.
CoRR, 2014

A Tutorial on Principal Component Analysis.
CoRR, 2014

Zero-Shot Learning by Convex Combination of Semantic Embeddings.
Proceedings of the 2nd International Conference on Learning Representations, 2014

2013
Using Web Co-occurrence Statistics for Improving Image Categorization.
CoRR, 2013

DeViSE: A Deep Visual-Semantic Embedding Model.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Fast, Accurate Detection of 100, 000 Object Classes on a Single Machine.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Modeling the impact of common noise inputs on the network activity of retinal ganglion cells.
J. Comput. Neurosci., 2012

Three Controversial Hypotheses Concerning Computation in the Primate Cortex.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2007
Estimating Information Rates with Confidence Intervals in Neural Spike Trains.
Neural Computation, 2007

2005
Estimating Entropy Rates with Bayesian Confidence Intervals.
Neural Computation, 2005


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