Sneha Bangalore

Method Policy gradient methods[1] have two components to them - the probability and the reward . The goal is to maximize the reward and increasing the probability of the action that leads to it, from the state. Different algorithms have tweaked the reward weight in the objective to try and...

Diffusion, a class of generative models, boils down to an MSE between added noise and network predicted noise. Why would learning to predict the noise help with image generation (which is what it is most used for)? How did we arrive at MSE? This post dives deep into the math...