Diederik P. Kingma
Diederik P. Kingma
Research Scientist, Google Brain
Verified email at google.com - Homepage
TitleCited byYear
Adam: A Method for Stochastic Optimization
DP Kingma, J Ba
Proceedings of the 3rd International Conference on Learning Representations …, 2014
367942014
Auto-Encoding Variational Bayes
DP Kingma, M Welling
Proceedings of the 2nd International Conference on Learning Representations …, 2013
75342013
Auto-encoding variational bayes (2013)
DP Kingma, M Welling
arXiv preprint arXiv:1312.6114, 2013
75072013
Semi-Supervised Learning with Deep Generative Models
DP Kingma, S Mohamed, DJ Rezende, M Welling
Advances in Neural Information Processing Systems, 3581-3589, 2014
12792014
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
6552016
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
5612016
A method for stochastic optimization. arXiv 2014
DP Kingma, JA Ba
arXiv preprint arXiv:1412.6980, 2019
4602019
Variational Dropout and the Local Reparameterization Trick
DP Kingma, T Salimans, M Welling
Advances in Neural Information Processing Systems 28 (NIPS 2015), 2015
4432015
Glow: Generative flow with invertible 1x1 convolutions
DP Kingma, P Dhariwal
Advances in Neural Information Processing Systems, 10215-10224, 2018
3352018
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
2872014
Variational lossy autoencoder
X Chen, DP Kingma, T Salimans, Y Duan, P Dhariwal, J Schulman, ...
arXiv preprint arXiv:1611.02731, 2016
2712016
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
2512017
Learning Sparse Neural Networks through Regularization
C Louizos, M Welling, DP Kingma
arXiv preprint arXiv:1712.01312, 2017
1452017
Stochastic gradient VB and the variational auto-encoder
DP Kingma, M Welling
Second International Conference on Learning Representations, ICLR, 2014
1222014
Ba J
DP Kingma
Adam: a method for stochastic optimization, 2014
1052014
Adam: A method for stochastic optimization. CoRR abs/1412.6980
DP Kingma, J Ba
932014
Adam: a method for stochastic optimization. arXiv
DP Kingma, J Ba
arXiv preprint arXiv:1412.6980 6, 2014
812014
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
512013
a method for stochastic optimization. arXiv preprint
DP Kingma, JB Adam
arXiv preprint arXiv:1412.6980, 2014
502014
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