3 papers
cs.LG2024
Diffusion Posterior Sampling is Computationally Intractable
Shivam Gupta, Ajil Jalal, Aditya Parulekar +2
Diffusion models are a remarkably effective way of learning and sampling from a distribution . In posterior sampling, one is also given a measurement model and…
cs.LG2023
Improved Sample Complexity Bounds for Diffusion Model Training
Shivam Gupta, Aditya Parulekar, Eric Price +1
Diffusion models have become the most popular approach to deep generative modeling of images, largely due to their empirical performance and reliability. From a theoretical standpo…
cs.LG2021
L1 Regression with Lewis Weights Subsampling
Aditya Parulekar, Advait Parulekar, Eric Price
We consider the problem of finding an approximate solution to regression while only observing a small number of labels. Given an unlabeled data matrix , we…