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Diederik P. Kingma
Diederik P. Kingma
Other namesDurk Kingma
Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Adam: A Method for Stochastic Optimization
DP Kingma, J Ba
Proceedings of the 3rd International Conference on Learning Representations …, 2014
1353242014
Auto-Encoding Variational Bayes
DP Kingma, M Welling
arXiv preprint arXiv:1312.6114, 2013
252732013
Semi-Supervised Learning with Deep Generative Models
DP Kingma, S Mohamed, DJ Rezende, M Welling
Advances in Neural Information Processing Systems, 3581-3589, 2014
28602014
Glow: Generative Flow with Invertible 1x1 Convolutions
DP Kingma, P Dhariwal
Advances in Neural Information Processing Systems, 10215-10224, 2018
21322018
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
17072016
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
16212016
Variational Dropout and the Local Reparameterization Trick
DP Kingma, T Salimans, M Welling
Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015
12982015
An Introduction to Variational Autoencoders
DP Kingma, M Welling
Foundations and Trends® in Machine Learning 12 (4), 307-392, 2019
12902019
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
8432017
Learning Sparse Neural Networks through Regularization
C Louizos, M Welling, DP Kingma
Proceedings of the International Conference on Learning Representations (ICLR), 2017
8372017
Variational Lossy Autoencoder
X Chen, DP Kingma, T Salimans, Y Duan, P Dhariwal, J Schulman, ...
arXiv preprint arXiv:1611.02731, 2016
6522016
Score-based generative modeling through stochastic differential equations
Y Song, J Sohl-Dickstein, DP Kingma, A Kumar, S Ermon, B Poole
arXiv preprint arXiv:2011.13456, 2020
6072020
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
5812014
Variational Autoencoders and Nonlinear ICA: A Unifying Framework
I Khemakhem, DP Kingma, A Hyvärinen
The 23rd International Conference on Artificial Intelligence and Statistics …, 2019
3002019
A method for stochastic optimization. arXiv preprint 2014
DP Kingma, BJ Adam
arXiv preprint arXiv:1412.6980 205, 2014
2772014
International Conference on Learning Representations
DP Kingma, J Ba
3rd International Conference on Learning Representations. ICLR 2015 …, 2015
2372015
VideoFlow: A Flow-Based Generative Model for Video
M Kumar, M Babaeizadeh, D Erhan, C Finn, S Levine, L Dinh, DP Kingma
Proceedings of the International Conference on Learning Representations (ICLR), 2019
182*2019
Variational Diffusion Models
D Kingma, T Salimans, B Poole, J Ho
Advances in neural information processing systems 34, 21696-21707, 2021
1662021
GPU Kernels for Block-Sparse Weights
S Gray, A Radford, DP Kingma
1432017
A MethodforStochasticOptimizaG tion
DP Kingma, BAJ Adam
Proceedingsofthe3rdInternationalConferenceon LearningRepresentations, 2015
1212015
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Articles 1–20