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Stephan Mandt

12 papers hereh-index 598 citations14 works total

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

author position
  • middle author3
  • last author9

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.LG9
  • cs.CV2
  • cs.CL1
same name
  • Stephan Mandt — 31 papers, h 21
  • Stephan Mandt — 8 papers, h 5
  • Stephan Mandt — 7 papers, h 3
  • Stephan Mandt — 6 papers, h 6
  • Stephan Mandt — 6 papers, h 7
  • Stephan Mandt — 4 papers, h 3

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
20232026
most citedHeavy-Tailed Diffusion Models

2 citations · 3 across the 12 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CV2026

Variational Test-time Optimization for Diffusion Synchronization

Hyunsoo Lee, Farrin Marouf Sofian, Kushagra Pandey +1

Collaborative generation, which coordinates multiple diffusion trajectories to extend the capabilities of pretrained priors, has emerged as a powerful paradigm for extending the ap…

cs.LG2026

Uncertainty Estimation for Molecular Diffusion Models

Paul Seij, Christian A. Naesseth, Stephan Mandt +1

Diffusion models have seen wide adoption for 3D molecular generation, yet they offer no principled signal of when a generated molecule is likely to be of low quality. We propose a…

cs.LG2026

Skipping the Zeros in Diffusion Models for Sparse Data Generation

Phil Sidney Ostheimer, Mayank Nagda, Andriy Balinskyy +6

Diffusion models (DMs) excel on dense continuous data, but are not designed for sparse continuous data. They do not model exact zeros that represent the deliberate absence of a sig…

cs.LG2026

Hierarchical Variational Policies for Reward-Guided Diffusion

Kushagra Pandey, Farrin Marouf Sofian, Jan Niklas Groeneveld +2

Adapting pretrained diffusion models to downstream objectives such as inverse problems often requires expensive test-time guidance or optimization. We propose a principled framewor…

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