DK
Diederik P. Kingma
cs.LGstat.MLcs.AIcs.CVstat.COcs.CLcs.NEcs.SDeess.AS
On Valency
published · living versionsW_d722f379·v1 · currentpublished
Semi-Supervised Learning with Deep Generative Models
with Danilo J. Rezende, Shakir Mohamed, Max Welling
1 version
Preprints & journals
28 papers in the corpus · 2013–2024EM Distillation for One-step Diffusion Models2405.16852v2 · Sirui Xie, Zhisheng Xiao, Diederik P Kingma et al.2024 · 1 citationarXiv
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation2303.00848v7 · Diederik P. Kingma, Ruiqi Gao2023 · 23 citationsarXiv
Variational Diffusion Models2107.00630v6 · Diederik P. Kingma, Tim Salimans, Ben Poole et al.2021 · 282 citationsarXiv
On Distillation of Guided Diffusion Models2210.03142v3 · Chenlin Meng, Robin Rombach, Ruiqi Gao et al.2022 · 309 citationsarXiv
Auto-Encoding Variational Bayes1312.6114v11 · Diederik P Kingma, Max Welling2013 · 15,134 citationsarXiv
Imagen Video: High Definition Video Generation with Diffusion Models2210.02303v1 · Jonathan Ho, William Chan, Chitwan Saharia et al.2022 · 346 citationsarXiv
Learning Energy-Based Models by Diffusion Recovery Likelihood2012.08125v2 · Ruiqi Gao, Yang Song, Ben Poole et al.2020 · 15 citationsarXiv
How to Train Your Energy-Based Models2101.03288v2 · Yang Song, Diederik P. Kingma2021 · 79 citationsarXiv
Score-Based Generative Modeling through Stochastic Differential Equations2011.13456v2 · Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma et al.2020 · 1,358 citationsarXiv
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesis2011.03568v2 · Ron J. Weiss, RJ Skerry-Ryan, Eric Battenberg et al.2020 · 81 citationsarXiv
Variational Autoencoders and Nonlinear ICA: A Unifying Framework1907.04809v4 · Ilyes Khemakhem, Diederik P. Kingma, Ricardo Pio Monti et al.2019 · 121 citationsProceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, pages 2207-2217, year 2020
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA2002.11537v4 · Ilyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma et al.2020 · 24 citationsarXiv
On Linear Identifiability of Learned Representations2007.00810v3 · Geoffrey Roeder, Luke Metz, Diederik P. Kingma2020 · 20 citationsarXiv
Flow Contrastive Estimation of Energy-Based Models1912.00589v2 · Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma et al.2019 · 68 citationsarXiv
An Introduction to Variational Autoencoders1906.02691v3 · Diederik P. Kingma, Max Welling2019 · 3,160 citationsFoundations and Trends in Machine Learning: Vol. 12 (2019): No. 4, pp 307-392
Glow: Generative Flow with Invertible 1x1 Convolutions1807.03039v2 · Diederik P. Kingma, Prafulla Dhariwal2018 · 177 citationsarXiv
Learning Sparse Neural Networks through $L_0$ Regularization1712.01312v2 · Christos Louizos, Max Welling, Diederik P. Kingma2017 · 148 citationsarXiv
Variational Lossy Autoencoder1611.02731v2 · Xi Chen, Diederik P. Kingma, Tim Salimans et al.2016 · 241 citationsarXiv
Improving Variational Inference with Inverse Autoregressive Flow1606.04934v2 · Diederik P. Kingma, Tim Salimans, Rafal Jozefowicz et al.2016 · 180 citationsarXiv
Adam: A Method for Stochastic Optimization1412.6980v9 · Diederik P. Kingma, Jimmy Ba2014 · 83,533 citationsarXiv
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications1701.05517v1 · Tim Salimans, Andrej Karpathy, Xi Chen et al.2017 · 614 citationsarXiv
Note on Equivalence Between Recurrent Neural Network Time Series Models and Variational Bayesian Models1504.08025v2 · Jascha Sohl-Dickstein, Diederik P. Kingma2015 · 1 citationarXiv
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks1602.07868v3 · Tim Salimans, Diederik P. Kingma2016 · 1,429 citationsarXivon Valency
Variational Dropout and the Local Reparameterization Trick1506.02557v2 · Diederik P. Kingma, Tim Salimans, Max Welling2015 · 440 citationsarXiv
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap1410.6460v4 · Tim Salimans, Diederik P. Kingma, Max Welling2014 · 384 citationsarXivon Valency
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets1402.0480v5 · Diederik P. Kingma, Max Welling2014 · 36 citationsProceedings of The 31st International Conference on Machine Learning, pp. 1782-1790, 2014
Semi-Supervised Learning with Deep Generative Models1406.5298v2 · Diederik P. Kingma, Danilo J. Rezende, Shakir Mohamed et al.2014 · 1,487 citationsarXivon Valency
Fast Gradient-Based Inference with Continuous Latent Variable Models in Auxiliary Form1306.0733v1 · Diederik P Kingma2013 · 28 citationsarXiv
Career total: 42 works. 28 are in this corpus.
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