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Found 4 papers, 2 papers with code
Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
To tackle this issue, we propose a new learning paradigm that integrates both paired and unpaired data $\textbf{seamlessly}$ through the data likelihood maximization techniques.
Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps
Diffusion distillation represents a highly promising direction for achieving faithful text-to-image generation in a few sampling steps.
Your Student is Better Than Expected: Adaptive Teacher-Student Collaboration for Text-Conditional Diffusion Models
While several powerful distillation methods were recently proposed, the overall quality of student samples is typically lower compared to the teacher ones, which hinders their practical usage.
Towards Real-time Text-driven Image Manipulation with Unconditional Diffusion Models
Finally, we show that our approach can adapt the pretrained model to the user-specified image and text description on the fly just for 4 seconds.
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