16 citations · 25 across the 10 of their papers we have counts for
3 papers · 1 filter
Categorical Reparameterization with Denoising Diffusion models
Samson Gourevitch, Alain Durmus, Eric Moulines +2
Learning models with categorical variables requires optimizing expectations over discrete distributions, a setting in which stochastic gradient-based optimization is challenging du…
Briding Diffusion Posterior Sampling and Monte Carlo methods: a survey
Yazid Janati, Alain Durmus, Jimmy Olsson +1
Diffusion models enable the synthesis of highly accurate samples from complex distributions and have become foundational in generative modeling. Recently, they have demonstrated si…
Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance
Badr Moufad, Yazid Janati, Alain Durmus +3
Classifier-Free Guidance (CFG) is a widely used technique for improving conditional diffusion models by linearly combining the outputs of conditional and unconditional denoisers. W…