Graphically Structured Diffusion Models

10/20/2022
by   Christian Weilbach, et al.
6

We introduce a framework for automatically defining and learning deep generative models with problem-specific structure. We tackle problem domains that are more traditionally solved by algorithms such as sorting, constraint satisfaction for Sudoku, and matrix factorization. Concretely, we train diffusion models with an architecture tailored to the problem specification. This problem specification should contain a graphical model describing relationships between variables, and often benefits from explicit representation of subcomputations. Permutation invariances can also be exploited. Across a diverse set of experiments we improve the scaling relationship between problem dimension and our model's performance, in terms of both training time and final accuracy.

READ FULL TEXT

page 2

page 7

page 11

page 12

page 13

research
07/04/2023

ProtoDiffusion: Classifier-Free Diffusion Guidance with Prototype Learning

Diffusion models are generative models that have shown significant advan...
research
12/07/2012

Layer-wise learning of deep generative models

When using deep, multi-layered architectures to build generative models ...
research
09/04/2017

Continuous-Time Flows for Deep Generative Models

Normalizing flows have been developed recently as a method for drawing s...
research
05/31/2022

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

Diffusion-based Deep Generative Models (DDGMs) offer state-of-the-art pe...
research
06/14/2023

Unbiased Learning of Deep Generative Models with Structured Discrete Representations

By composing graphical models with deep learning architectures, we learn...
research
08/05/2018

A Review of Learning with Deep Generative Models from perspective of graphical modeling

This document aims to provide a review on learning with deep generative ...
research
08/15/2022

Applying Regularized Schrödinger-Bridge-Based Stochastic Process in Generative Modeling

Compared to the existing function-based models in deep generative modeli...

Please sign up or login with your details

Forgot password? Click here to reset