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Didrik Nielsen
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2020 – today
- 2022
- [j1]Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi:
Diffusion Models for Video Prediction and Infilling. Trans. Mach. Learn. Res. 2022 (2022) - [i10]Giorgio Giannone, Didrik Nielsen, Ole Winther:
Few-Shot Diffusion Models. CoRR abs/2205.15463 (2022) - [i9]Tobias Höppe, Arash Mehrjou
, Stefan Bauer, Didrik Nielsen, Andrea Dittadi:
Diffusion Models for Video Prediction and Infilling. CoRR abs/2206.07696 (2022) - 2021
- [c7]Priyank Jaini, Didrik Nielsen, Max Welling:
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC. AISTATS 2021: 3349-3357 - [c6]Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling:
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions. NeurIPS 2021: 12454-12465 - [i8]Priyank Jaini, Didrik Nielsen, Max Welling:
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC. CoRR abs/2102.02374 (2021) - [i7]Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling:
Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models. CoRR abs/2102.05379 (2021) - 2020
- [c5]Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling:
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. NeurIPS 2020 - [c4]Didrik Nielsen, Ole Winther:
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. NeurIPS 2020 - [i6]Didrik Nielsen, Ole Winther:
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. CoRR abs/2002.02547 (2020) - [i5]Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling:
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. CoRR abs/2007.02731 (2020)
2010 – 2019
- 2018
- [c3]Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava:
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam. ICML 2018: 2616-2625 - [c2]Mohammad Emtiyaz Khan, Didrik Nielsen:
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models. ISITA 2018: 31-35 - [c1]Aaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark Schmidt, Mohammad Emtiyaz Khan:
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient. NeurIPS 2018: 6248-6258 - [i4]Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava:
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam. CoRR abs/1806.04854 (2018) - [i3]Mohammad Emtiyaz Khan, Didrik Nielsen:
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models. CoRR abs/1807.04489 (2018) - [i2]Aaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark Schmidt, Mohammad Emtiyaz Khan:
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient. CoRR abs/1811.04504 (2018) - 2017
- [i1]Mohammad Emtiyaz Khan, Wu Lin, Voot Tangkaratt, Zuozhu Liu, Didrik Nielsen:
Variational Adaptive-Newton Method for Explorative Learning. CoRR abs/1711.05560 (2017)
Coauthor Index
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