Our NeurIPS paper got accepted with spotlight mentioning

Today we’re very happy to share that our paper on stochastic optimal control, which we developed in collaboration with colleagues from Karlsruher Institut für Technologie (KIT), NVIDIA, Microsoft Research and Cornell University has been accepted to NeurIPS 2025.
The paper with the title “Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference” explores how a trust-region-based optimization algorithm performs for applications of stochastic optimal control against existing methods.
We could show that our novel method can improve tasks like fine-tuning diffusion models, diffusion-based sampling or transition path sampling.
A big thank you to all contributors (Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann) and congratulations to the team on receiving a spotlight mentioning!
The paper can be found here: https://arxiv.org/pdf/2508.12511