Diffusion models
Diffusion-based language models have recently emerged as a promising alternative to autoregressive generation, yet their reliance on …
We present significant extensions to diffusion-based language models, blurring the line with autoregressive ones. We introduce …
We present significant extensions to diffusion-based sequence generation models, blurring the line with autoregressive language models. …
We propose Adaptive Diffusion Denoised Smoothing, a method for certifying the predictions of a vision model against adversarial …
We take significant steps toward unifying autoregressive and diffusion-based sequence generation by extending the SEDD discrete …
In model-based optimisation (MBO) we are interested in using machine learning to design candidates that maximise some measure of reward …
Text-conditioned image generation models have recently shown immense qualitative success using denoising diffusion processes. However, …
We extend score-based generative diffusion processes (GDPs) to sparse graphs and other inherently discrete data, with a focus on …
Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be …