Diederik P. Kingma
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
12
Venues
5
Active years
2014–2025
Best venue rank
A*
Where they publish
Papers
12 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Adam-mini: Use Fewer Learning Rates To Gain More. | Yushun Zhang, Congliang Chen, Ziniu Li, Tian Ding, Chenwei Wu, Diederik P. Kingma, Yinyu Ye, Zhi-Quan Luo, Ruoyu Sun |
| 2023 | CVPR | On Distillation of Guided Diffusion Models. | Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans |
| 2021 | ICASSP | Wave-Tacotron: Spectrogram-Free End-to-End Text-to-Speech Synthesis. | Ron J. Weiss, R. J. Skerry-Ryan, Eric Battenberg, Soroosh Mariooryad, Diederik P. Kingma |
| 2021 | ICLR | Score-Based Generative Modeling through Stochastic Differential Equations. | Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole |
| 2021 | ICLR | Learning Energy-Based Models by Diffusion Recovery Likelihood. | Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma |
| 2020 | AISTATS | Variational Autoencoders and Nonlinear ICA: A Unifying Framework. | Ilyes Khemakhem, Diederik P. Kingma, Ricardo Pio Monti, Aapo Hyvrinen |
| 2020 | CVPR | Flow Contrastive Estimation of Energy-Based Models. | Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu |
| 2018 | ICLR | Learning Sparse Neural Networks through L_0 Regularization. | Christos Louizos, Max Welling, Diederik P. Kingma |
| 2017 | ICLR | Variational Lossy Autoencoder. | Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel |
| 2017 | ICLR | PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. | Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma |
| 2015 | ICML | Markov Chain Monte Carlo and Variational Inference: Bridging the Gap. | Tim Salimans, Diederik P. Kingma, Max Welling |
| 2014 | ICML | Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets. | Diederik P. Kingma, Max Welling |