Imagine Networks

11/04/2021
by   Seokjun Kim, et al.
0

In this paper, we introduce an Imagine Network that can simulate itself through graph tree neural networks. Among the graph tree neural networks models, association, deduction, and memory networks are learned, and a network is created by combining the discriminator and reinforcement learning models. This model can learn various datasets or data samples generated in environments and generate new data samples.

READ FULL TEXT

page 3

page 4

research
11/02/2021

Graph Tree Deductive Networks

In this paper, we introduce Graph Tree Deductive Networks, a network tha...
research
06/09/2021

XBNet : An Extremely Boosted Neural Network

Neural networks have proved to be very robust at processing unstructured...
research
12/09/2019

Combining Networks using Cherry Picking Sequences

Phylogenetic networks are important for the study of evolution. The numb...
research
06/22/2020

Graph Neural Networks and Reinforcement Learning for Behavior Generation in Semantic Environments

Most reinforcement learning approaches used in behavior generation utili...
research
11/12/2021

deepstruct – linking deep learning and graph theory

deepstruct connects deep learning models and graph theory such that diff...
research
10/06/2021

Generative Optimization Networks for Memory Efficient Data Generation

In standard generative deep learning models, such as autoencoders or GAN...
research
11/01/2022

Wavelet Neural Networks versus Wavelet-based Neural Networks

This is the first paper in a sequence of studies in which we introduce a...

Please sign up or login with your details

Forgot password? Click here to reset