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researcher

Jan Kautz

15 papers hereh-index 154.3k citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author8
  • last author6

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.LG8
  • cs.CV3
  • stat.ML2
  • cs.AI1
  • eess.IV1
same name
  • Jan Kautz — 91 papers, h 44
  • Jan Kautz — 40 papers, h 30
  • Jan Kautz — 27 papers, h 21
  • Jan Kautz — 24 papers, h 24
  • Jan Kautz — 20 papers, h 18
  • Jan Kautz — 15 papers, h 17

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedNVAE: A Deep Hierarchical Variational Autoencoder

372 citations · 477 across the 12 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

eess.IV2023

SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models

Batu Ozturkler, Chao Liu, Benjamin Eckart +3

Diffusion models have recently gained popularity for accelerated MRI reconstruction due to their high sample quality. They can effectively serve as rich data priors while incorpora…

cs.LG2023★ 16 cited

Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling

Morteza Mardani, Noah Brenowitz, Yair Cohen +10

The state of the art for physical hazard prediction from weather and climate requires expensive km-scale numerical simulations driven by coarser resolution global inputs. Here, a g…

cs.LG2023★ 37 cited

A Variational Perspective on Solving Inverse Problems with Diffusion Models

Morteza Mardani, Jiaming Song, Jan Kautz +1

Diffusion models have emerged as a key pillar of foundation models in visual domains. One of their critical applications is to universally solve different downstream inverse tasks…

cs.LG2023★ 6 cited

Score-based Diffusion Models in Function Space

Jae Hyun Lim, Nikola B. Kovachki, Ricardo Baptista +10

Diffusion models have recently emerged as a powerful framework for generative modeling. They consist of a forward process that perturbs input data with Gaussian white noise and a r…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.