Jeffrey Pennington - Concepedia

Author

Jeffrey Pennington

Also Known As

Dauphin, Yann, Gur, Izzeddin, Hu, Hong, J. Pennington, J. S. Pennington, Jeffrey Pennington, Jeffrey S Pennington, Pennington, Jeffrey, Pennington, Jeffrey S., Raesz-Martinez, Robin A.

Publications

37.7K

Citations

H-Index

Concepts

All Affiliations

Google (United States)Stanford University Philadelphia University University of Pennsylvania SLAC National Accelerator Laboratory

About

Jeffrey Pennington is an author at Google (United States) specializing in machine learning, engineering, and deep learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	25	33	35.7K
2	Medicine	2	3	44
3	Health Sciences	1	1	12
4	Language Studies	1	1	33.2K
5	Natural Sciences	1	1	23

Jeffrey Pennington

Publications

37.5K

Citations

H-Index

Page 1

	Year	Citations
Glove: Global Vectors for Word Representation Jeffrey Pennington, Richard Socher, Christopher D. Manning EngineeringMachine LearningVector SpaceCorpus LinguisticsText Mining	2014	33.2K
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions Richard Socher, Jeffrey Pennington, Eric Huang,	2011	1.2K
Deep Neural Networks as Gaussian Processes Jaehoon Lee, Yasaman Bahri, Roman Novak, arXiv (Cornell University) Artificial IntelligenceGeometric LearningConvolutional Neural NetworkDeep Neural NetworksEngineering	2017	335
Deep Neural Networks as Gaussian Processes Jaehoon Lee, Yasaman Bahri, Roman Novak, arXiv (Cornell University) Artificial IntelligenceGeometric LearningConvolutional Neural NetworkDeep Neural NetworksEngineering	2018	313
Statistical Mechanics of Deep Learning Yasaman Bahri, Jonathan Kadmon, Jeffrey Pennington, Annual Review of Condensed Matter Physics Geometric LearningDeep Neural NetworksStatistical MechanicsMachine LearningData Science	2019	234
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak, Yasaman Bahri, Daniel A. Abolafia, arXiv (Cornell University) Artificial IntelligencePoor GeneralizationNeural Scaling LawHyperparameter EstimationEngineering	2018	224
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train\n 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao, Yasaman Bahri, Jascha Sohl‐Dickstein, arXiv (Cornell University)	2018	175
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Roman Novak, Lechao Xiao, Jaehoon Lee, arXiv (Cornell University) Artificial IntelligenceNeural Scaling LawConvolutional Neural NetworkBayesian StatisticEngineering	2018	169
Leading singularities and off-shell conformal integrals J. M. Drummond, Claude Duhr, Burkhard Eden, Journal of High Energy Physics Conformal IntegralsPhysicsOff-shell Conformal IntegralsUnknown IntegralsQuantum Field Theory	2013	132
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli Neural Information Processing Systems Artificial IntelligenceGeometric LearningJacobian Singular ValuesConvolutional Neural NetworkEngineering	2017	102

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