Diederik P. Kingma

University of Florida — United States

Computer Science · Physical Sciences

31h-index163.0kcitations48works679.72yr avg
OpenAlex↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Generative Adversarial Networks and Image Synthesis(26), Gaussian Processes and Bayesian Inference(15), Model Reduction and Neural Networks(11), Neural Networks and Applications(9), Domain Adaptation and Few-Shot Learning(6)

Publications48 total

Fast Kd-Trees for the Kullback-Leibler Divergence and Other Decomposable Bregman Divergences
UvA-DARE (University of Amsterdam)·2025· 2.0k citedOpen Access
EM Distillation for One-step Diffusion Models
arXiv (Cornell University)·2024Open Access
EM Distillation for One-step Diffusion Models
2024
On Distillation of Guided Diffusion Models
2023· 234 cited
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
arXiv (Cornell University)·2023· 12 citedOpen Access
On Distillation of Guided Diffusion Models
arXiv (Cornell University)·2022· 8 citedOpen Access
Imagen Video: High Definition Video Generation with Diffusion Models
arXiv (Cornell University)·2022· 345 citedOpen Access
On Density Estimation with Diffusion Models
Neural Information Processing Systems·2021· 1 cited
Variational Diffusion Models
arXiv (Cornell University)·2021· 282 citedOpen Access
Wave-Tacotron: Spectrogram-Free End-to-End Text-to-Speech Synthesis
2021· 10 citedOpen Access
On Linear Identifiability of Learned Representations
International Conference on Machine Learning·2021· 3 cited
Score-Based Generative Modeling through Stochastic Differential Equations
International Conference on Learning Representations·2021· 73 cited
How to Train Your Energy-Based Models
arXiv (Cornell University)·2021· 81 citedOpen Access
Untitled
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)·2021· 49.9k citedOpen Access
Learning Energy-Based Models by Diffusion Recovery Likelihood
arXiv (Cornell University)·2020· 15 citedOpen Access
Score-Based Generative Modeling through Stochastic Differential Equations
arXiv (Cornell University)·2020· 1.3k citedOpen Access
On Linear Identifiability of Learned Representations
arXiv (Cornell University)·2020· 16 citedOpen Access
Flow Contrastive Estimation of Energy-Based Models
2020· 63 cited
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models.
Työväentutkimus Vuosikirja·2020· 14 citedOpen Access
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
arXiv (Cornell University)·2020· 25 citedOpen Access
page 1 of 3Next →

Frequent Co-authors

Tim Salimans(17), Max Welling(14), Ben Poole(8), Ruiqi Gao(7), Jascha Sohl‐Dickstein(4), Stefano Ermon(4), Yang Song(3), Jonathan Ho(3), Ilya Sutskever(3), Ilyes Khemakhem(3), Ricardo Pio Monti(3), Aapo Hyvärinen(3), Jimmy Ba(2), Abhishek Kumar(2), Andrej Karpathy(2), Jonathan Ho(2), Prafulla Dhariwal(2), Chenlin Meng(2), Rafał Józefowicz(2), Xi Chen(2)