Diederik P. Kingma - Google Scholar Citations

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	All	Since 2015
Citations	49859	49410
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i10-index	29	29

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Jimmy BaUniversity of TorontoVerified email at cs.toronto.edu
Max WellingProfessor Machine Learning, University of AmsterdamVerified email at uva.nl
Tim SalimansGoogle Brain AmsterdamVerified email at google.com
Ilya SutskeverCo-Founder and Chief Scientist of OpenAIVerified email at openai.com
Prafulla DhariwalResearcher, OpenAIVerified email at openai.com
Shakir MohamedSenior Staff Scientist, DeepMindVerified email at deepmind.com
Danilo Jimenez RezendeSenior Staff Research Scientist at DeepMindVerified email at google.com
Pieter AbbeelUC Berkeley | Covariant.AIVerified email at cs.berkeley.edu
John SchulmanResearch Scientist, OpenAIVerified email at openai.com
Yan DuanEmbodied Intelligence, UC BerkeleyVerified email at berkeley.edu
Christos LouizosPh.D. Candidate, University of AmsterdamVerified email at uva.nl
Alec RadfordOpenAIVerified email at openai.com
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
Dumitru ErhanStaff Research Scientist, Google BrainVerified email at google.com
Mohammad BabaeizadehUniversity of Illinois at Urbana–ChampaignVerified email at uiuc.edu
Manoj KumarGoogle BrainVerified email at google.com
Laurent DinhGoogle AIVerified email at google.com
Chelsea FinnStanford University, GoogleVerified email at cs.stanford.edu
Aapo HyvarinenINRIA & University of HelsinkiVerified email at helsinki.fi
Ilyes KhemakhemPhD student, Gatsby Unit, UCLVerified email at gatsby.ucl.ac.uk

Diederik P. Kingma

Research Scientist, Google Brain

Verified email at google.com - Homepage

Machine Learning Bayesian Inference Deep Learning Neural Networks


Title	Cited by	Year
Adam: A Method for Stochastic Optimization DP Kingma, J Ba Proceedings of the 3rd International Conference on Learning Representations …, 2014	36794	2014
Auto-Encoding Variational Bayes DP Kingma, M Welling Proceedings of the 2nd International Conference on Learning Representations …, 2013	7534	2013
Auto-encoding variational bayes (2013) DP Kingma, M Welling arXiv preprint arXiv:1312.6114, 2013	7507	2013
Semi-Supervised Learning with Deep Generative Models DP Kingma, S Mohamed, DJ Rezende, M Welling Advances in Neural Information Processing Systems, 3581-3589, 2014	1279	2014
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks T Salimans, DP Kingma Advances in Neural Information Processing Systems, 901-901, 2016	655	2016
Improved Variational Inference with Inverse Autoregressive Flow DP Kingma, T Salimans, R Jozefowicz, X Chen, I Sutskever, M Welling Advances in Neural Information Processing Systems, 4743-4751, 2016	561	2016
A method for stochastic optimization. arXiv 2014 DP Kingma, JA Ba arXiv preprint arXiv:1412.6980, 2019	460	2019
Variational Dropout and the Local Reparameterization Trick DP Kingma, T Salimans, M Welling Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015	443	2015
Glow: Generative flow with invertible 1x1 convolutions DP Kingma, P Dhariwal Advances in Neural Information Processing Systems, 10215-10224, 2018	335	2018
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap T Salimans, DP Kingma, M Welling Proceedings of the International Conference on Machine Learning (ICML), 2014	287	2014
Variational lossy autoencoder X Chen, DP Kingma, T Salimans, Y Duan, P Dhariwal, J Schulman, ... arXiv preprint arXiv:1611.02731, 2016	271	2016
Pixelcnn++: Improving the pixelcnn with discretized logistic mixture likelihood and other modifications T Salimans, A Karpathy, X Chen, DP Kingma arXiv preprint arXiv:1701.05517, 2017	251	2017
Learning Sparse Neural Networks through Regularization C Louizos, M Welling, DP Kingma arXiv preprint arXiv:1712.01312, 2017	145	2017
Stochastic gradient VB and the variational auto-encoder DP Kingma, M Welling Second International Conference on Learning Representations, ICLR, 2014	122	2014
Ba J DP Kingma Adam: a method for stochastic optimization, 2014	105	2014
Adam: A method for stochastic optimization. CoRR abs/1412.6980 DP Kingma, J Ba	93	2014
Adam: a method for stochastic optimization. arXiv DP Kingma, J Ba arXiv preprint arXiv:1412.6980 6, 2014	81	2014
A method for stochastic optimization. arXiv preprint. 2014 DP Kingma, BJ Adam arXiv preprint arXiv:1412.6980, 0	57
Auto-encoding variational bayes. arXiv 2013 DP Kingma, M Welling arXiv preprint arXiv:1312.6114, 2013	51	2013
a method for stochastic optimization. arXiv preprint DP Kingma, JB Adam arXiv preprint arXiv:1412.6980, 2014	50	2014

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