https://prnvbh.github.io/tags/generative-model/Recent content in Generative-Model on Pranav's BlogHugoen-usMon, 18 May 2026 00:00:00 +0000https://prnvbh.github.io/posts/knowledge-is-all-you-need/Mon, 18 May 2026 00:00:00 +0000https://prnvbh.github.io/posts/knowledge-is-all-you-need/<p>So far, I&rsquo;ve written about three types of generative models: GAN, VAE, and Flow-based models. They have shown great success in generating high-quality samples.</p> <h2 id="what-are-diffusion-models">What are Diffusion Models?</h2> <p>Diffusion models are inspired by non-equilibrium thermodynamics. They define a Markov chain of diffusion steps to slowly add random noise to data&hellip;</p> $$ q(\mathbf{x}_{t-1} \vert \mathbf{x}_t, \mathbf{x}_0) = \mathcal{N}(\mathbf{x}_{t-1}; \color{blue}{\tilde{\boldsymbol{\mu}}}(\mathbf{x}_t, \mathbf{x}_0), \color{red}{\tilde{\beta}_t} \mathbf{I}) $$$$ \begin{aligned} q(\mathbf{x}_{t-1} \vert \mathbf{x}_t, \mathbf{x}_0) &= q(\mathbf{x}_t \vert \mathbf{x}_{t-1}, \mathbf{x}_0) \frac{ q(\mathbf{x}_{t-1} \vert \mathbf{x}_0) }{ q(\mathbf{x}_t \vert \mathbf{x}_0) } \end{aligned} $$<p style="text-align: center;"> <img src="https://prnvbh.github.io/assets/post_1/yo.png" alt="Diffusion models" style="width: 100%; max-width: 800px;"> <br> <small><em>Figure 1: Overview of different types of generative models.</em></small> </p>