# Jeffrey Pennington

According to our database

Collaborative distances:

^{1}, Jeffrey Pennington authored at least 19 papers between 2011 and 2018.Collaborative distances:

## Timeline

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#### On csauthors.net:

## Bibliography

2018

Bayesian Convolutional Neural Networks with Many Channels are Gaussian Processes.

CoRR, 2018

Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks.

CoRR, 2018

Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10, 000-Layer Vanilla Convolutional Neural Networks.

CoRR, 2018

The Emergence of Spectral Universality in Deep Networks.

CoRR, 2018

Sensitivity and Generalization in Neural Networks: an Empirical Study.

CoRR, 2018

Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10, 000-Layer Vanilla Convolutional Neural Networks.

Proceedings of the 35th International Conference on Machine Learning, 2018

Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks.

Proceedings of the 35th International Conference on Machine Learning, 2018

The emergence of spectral universality in deep networks.

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice.

CoRR, 2017

Deep Neural Networks as Gaussian Processes.

CoRR, 2017

A Correspondence Between Random Neural Networks and Statistical Field Theory.

CoRR, 2017

Nonlinear random matrix theory for deep learning.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Geometry of Neural Network Loss Surfaces via Random Matrix Theory.

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Clinical Data Research Network Lessons Learned.

Proceedings of the Summit on Clinical Research Informatics, 2016

2015

Spherical Random Features for Polynomial Kernels.

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Glove: Global Vectors for Word Representation.

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2011

Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection.

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions.

Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, 2011