Apr 13, 2020 · The framework is evaluated using three applications; namely, language modeling, disentangled representation learning, and image generation. The ...
This paper proposes a novel controllable variational autoen- coder, ControlVAE 1, that leverages automatic control to precisely control the trade-off between ...
This repo is for our paper "ControlVAE: Controllable Variational Autoencoder" published at ICML 2020. It can be used for text generation, image generation ...
ControlVAE is a variational autoencoder (VAE) framework that combines the automatic control theory with the basic VAE to stabilize the KL-divergence of VAE ...
The Controllable Variational Autoencoder (ControlVAE) combines automatic control theory with the basic VAE model to manipulate the KL-divergence for ...
A new non-linear PI controller is designed, a variant of the proportional-integral-derivative (PID) control, to automatically tune the hyperparameter ...
Abstract: The Controllable Variational Autoencoder (ControlVAE) combines automatic control theory with the basic VAE model to manipulate the KL-divergence ...
In this paper, we introduce ControlVAE, a novel model-based framework for learning generative motion control policies based on variational autoencoders (VAE).
ControlVAE: Controllable Variational Autoencoder. 1. University of Illinois at ... Propose a new controllable VAE, ControlVAE, that combines a PI controller ...
A new non-linear PI controller is designed, a variant of the proportional-integral-derivative (PID) control, to automatically tune the hyperparameter ...
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