Experimenting with autoregressive flows in TensorFlow Likelihood

Experimenting with autoregressive flows in TensorFlow Likelihood

Byflorenc85

Within the first a part of this mini-series on autoregressive circulation fashions, we checked out bijectors in TensorFlow Likelihood (TFP), and noticed how you can use them for sampling and density estimation. We singled out the affine bijector to exhibit the mechanics of circulation development: We begin from a distribution that’s simple to pattern from,…

Eliminating Vector Quantization: Diffusion-Primarily based Autoregressive AI Fashions for Picture Era

Eliminating Vector Quantization: Diffusion-Primarily based Autoregressive AI Fashions for Picture Era

Byflorenc85

Autoregressive picture technology fashions have historically relied on vector-quantized representations, which introduce a number of important challenges. The method of vector quantization is computationally intensive and infrequently ends in suboptimal picture reconstruction high quality. This reliance limits the fashions’ flexibility and effectivity, making it troublesome to precisely seize the advanced distributions of steady picture information….