A TensorFlow implementation of "Sequence Modeling with Hierarchical Deep Generative Models with Dual Memory" (published in CIKM2017).
-
Updated
Oct 20, 2019 - Python
A TensorFlow implementation of "Sequence Modeling with Hierarchical Deep Generative Models with Dual Memory" (published in CIKM2017).
Covering Advanced Topics in Deep Learning for Natural Language Processing.
This is a Tensorflow implementation of the End-to-End Memory Network applied to Sequential Modelling of Facebook comments.
Implementation of a MemN2N model for question answering tasks
Use end-to-end memory networks architecture for Question & Answering NLP system
This is a repository that has my work on Memory Networks using various libraries
Files from NLP Project
Implementation of Dynamic Memory Networks for QA System using Tensorflow
This is my implementation of minimum memory network using pytorch
The implementation of the key-value memory network in Python/TensorFlow
Simplest end to end memory network implemented in tensorflow
Scene generation from novel viewpoints - Graph element networks
End-To-End Memory Network using Tensorflow
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems
Add a description, image, and links to the memory-network topic page so that developers can more easily learn about it.
To associate your repository with the memory-network topic, visit your repo's landing page and select "manage topics."