activity
20232026
most citedHeavy-Tailed Diffusion Models

2 citations · 2 across the 5 of their papers we have counts for

collaborators

9 papers

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

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…

cs.LG2025

Control-Augmented Autoregressive Diffusion for Data Assimilation

Prakhar Srivastava, Farrin Marouf Sofian, Francesco Immorlano +2

Despite advances in test-time scaling and diffusion finetuning, guidance for Auto-Regressive Diffusion Models (ARDMs) remains underexplored. We introduce an amortized framework tha…

cs.LG2025

Variational Control for Guidance in Diffusion Models

Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler +2

Diffusion models exhibit excellent sample quality, but existing guidance methods often require additional model training or are limited to specific tasks. We revisit guidance in di…

cs.LG20242 cited

Heavy-Tailed Diffusion Models

Kushagra Pandey, Jaideep Pathak, Yilun Xu +4

Diffusion models achieve state-of-the-art generation quality across many applications, but their ability to capture rare or extreme events in heavy-tailed distributions remains unc…

cs.CV2024

Fast Samplers for Inverse Problems in Iterative Refinement Models

Kushagra Pandey, Ruihan Yang, Stephan Mandt

Constructing fast samplers for unconditional diffusion and flow-matching models has received much attention recently; however, existing methods for solving inverse problems, such a…