Nielsen, Didrik

9 publications

TMLR 2022 Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

NeurIPSW 2022 Diffusion Models for Video Prediction and Infilling Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi

NeurIPSW 2022 Few-Shot Diffusion Models Giorgio Giannone, Didrik Nielsen, Ole Winther

AISTATS 2021 Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC Priyank Jaini, Didrik Nielsen, Max Welling

NeurIPS 2021 Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling

NeurIPS 2020 Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow Didrik Nielsen, Ole Winther

NeurIPS 2020 SurVAE Flows: Surjections to Bridge the Gap Between VAEs and Flows Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling

ICML 2018 Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava

NeurIPS 2018 SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient Aaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark Schmidt, Mohammad Emtiyaz Khan