Diederik P. Kingma - Concepedia

Author

Diederik P. Kingma

Also Known As

Diederik Kingma, Diederik P. Kingma, Gao, Ruiqi, Kingma, Diederik P, Kingma, Diederik P., Mandi, Jayanta, P. Kingma Diederik, Pham, Tuyen

Publications

163K

Citations

H-Index

Concepts

All Affiliations

Google (United States)University of Amsterdam Stanford University OpenAI (United States)

About

Diederik P. Kingma is an author at Google (United States) specializing in engineering, machine learning, and deep learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	25	30	107.8K
2	Data Science	22	25	107.2K
3	Computer Science	21	25	106.8K
4	Language Studies	1	1	10
5	Computer Engineering	1	1	149

Diederik P. Kingma

Publications

110.8K

Citations

H-Index

Page 1

	Year	Citations
Adam: A Method for Stochastic Optimization Diederik P. Kingma, Jimmy Ba UvA-DARE (University of Amsterdam) Artificial IntelligenceMathematical ProgrammingModel OptimizationMachine VisionMachine Learning	2014	84.5K
Auto-Encoding Variational Bayes Diederik P. Kingma, Max Welling UvA-DARE (University of Amsterdam) Structured PredictionAuto-encoding Variational BayesMachine LearningEngineeringAutoencoders	2013	15.5K
An Introduction to Variational Autoencoders Diederik P. Kingma, Max Welling Foundations and Trends® in Machine Learning	2019	2.3K
Semi-Supervised Learning with Deep Generative Models Diederik P. Kingma, Max Welling arXiv (Cornell University) Natural Language ProcessingGenerative SystemEngineeringMachine LearningData Science	2014	1.5K
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song, Jascha Sohl‐Dickstein, Diederik P. Kingma, arXiv (Cornell University) EngineeringMachine LearningData ScienceUncertainty QuantificationNumerical Sde Solvers	2020	1.3K
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans, Diederik P. Kingma arXiv (Cornell University) Structured PredictionConvolutional Neural NetworkEngineeringMachine LearningBatch Normalization	2016	927
Weight normalization: a simple reparameterization to accelerate training of deep neural networks Tim Salimans, Diederik P. Kingma Neural Information Processing Systems Structured PredictionConvolutional Neural NetworkEngineeringMachine LearningBatch Normalization	2016	715
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture\n Likelihood and Other Modifications Tim Salimans, Andrej Karpathy, Xi Chen, arXiv (Cornell University)	2017	567
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma, Tim Salimans, Max Welling arXiv (Cornell University) Gaussian DropoutEngineeringMachine LearningData ScienceDropout Rates	2015	460
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap Tim Salimans, Diederik P. Kingma, Max Welling arXiv (Cornell University) EngineeringMachine LearningData ScienceUncertainty QuantificationStatistical Inference	2014	358

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