Deep Generative Models with Learnable Knowledge Constraints

06/26/2018
by   Zhiting Hu, et al.
4

The broad set of deep generative models (DGMs) has achieved remarkable advances. However, it is often difficult to incorporate rich structured domain knowledge with the end-to-end DGMs. Posterior regularization (PR) offers a principled framework to impose structured constraints on probabilistic models, but has limited applicability to the diverse DGMs that can lack a Bayesian formulation or even explicit density evaluation. PR also requires constraints to be fully specified a priori, which is impractical or suboptimal for complex knowledge with learnable uncertain parts. In this paper, we establish mathematical correspondence between PR and reinforcement learning (RL), and, based on the connection, expand PR to learn constraints as the extrinsic reward in RL. The resulting algorithm is model-agnostic to apply to any DGMs, and is flexible to adapt arbitrary constraints with the model jointly. Experiments on human image generation and templated sentence generation show models with learned knowledge constraints by our algorithm greatly improve over base generative models.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/10/2019

Multi-objects Generation with Amortized Structural Regularization

Deep generative models (DGMs) have shown promise in image generation. Ho...
research
06/06/2021

On Memorization in Probabilistic Deep Generative Models

Recent advances in deep generative models have led to impressive results...
research
09/20/2020

Factorized Deep Generative Models for Trajectory Generation with Spatiotemporal-Validity Constraints

Trajectory data generation is an important domain that characterizes the...
research
09/27/2022

What Does DALL-E 2 Know About Radiology?

Generative models such as DALL-E 2 could represent a promising future to...
research
06/10/2019

Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards

Generating keyphrases that summarize the main points of a document is a ...
research
05/10/2020

Posterior Control of Blackbox Generation

Text generation often requires high-precision output that obeys task-spe...
research
04/30/2019

Performing Structured Improvisations with pre-trained Deep Learning Models

The quality of outputs produced by deep generative models for music have...

Please sign up or login with your details

Forgot password? Click here to reset