More from the Same Authors

• 2022 : On Distillation of Guided Diffusion Models »
  Chenlin Meng · Ruiqi Gao · Diederik Kingma · Stefano Ermon · Jonathan Ho · Tim Salimans
• 2021 Poster: Variational Diffusion Models »
  Diederik Kingma · Tim Salimans · Ben Poole · Jonathan Ho
• 2020 Poster: ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA »
  Ilyes Khemakhem · Ricardo Monti · Diederik Kingma · Aapo Hyvarinen
• 2020 Spotlight: ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA »
  Ilyes Khemakhem · Ricardo Monti · Diederik Kingma · Aapo Hyvarinen
• 2018 Poster: Glow: Generative Flow with Invertible 1x1 Convolutions »
  Diederik Kingma · Prafulla Dhariwal
• 2017 Workshop: Bayesian Deep Learning »
  Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Andrew Wilson · Andrew Wilson · Diederik Kingma · Zoubin Ghahramani · Kevin Murphy · Max Welling
• 2016 Poster: Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks »
  Tim Salimans · Diederik Kingma
• 2016 Oral: Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks »
  Tim Salimans · Diederik Kingma
• 2016 Poster: Improving Variational Autoencoders with Inverse Autoregressive Flow »
  Diederik Kingma · Tim Salimans · Rafal Jozefowicz · Peter Chen · Xi Chen · Ilya Sutskever · Max Welling
• 2015 Poster: Variational Dropout and the Local Reparameterization Trick »
  Diederik Kingma · Tim Salimans · Max Welling
• 2014 Poster: Semi-supervised Learning with Deep Generative Models »
  Diederik Kingma · Shakir Mohamed · Danilo Jimenez Rezende · Max Welling
• 2014 Spotlight: Semi-supervised Learning with Deep Generative Models »
  Diederik Kingma · Shakir Mohamed · Danilo Jimenez Rezende · Max Welling
• 2010 Poster: Regularized estimation of image statistics by Score Matching »
  Diederik Kingma · Yann LeCun