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Found 3 papers, 2 papers with code
Disentangled Representation Learning with the Gromov-Monge Gap
However, matching the prior while preserving geometric features is challenging, as a mapping that fully preserves these features while aligning the data distribution with the prior does not exist in general.
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization
Moreover, given the same computational resources, a ReNO-optimized one-step model outperforms widely-used open-source models such as SDXL and PixArt-$\alpha$, highlighting the efficiency and effectiveness of ReNO in enhancing T2I model performance at inference time.
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
We hence establish UOT-FM as a principled method for unpaired image translation.
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