Memory Network

Introduced by Weston et al. in Memory Networks

A Memory Network provides a memory component that can be read from and written to with the inference capabilities of a neural network model. The motivation is that many neural networks lack a long-term memory component, and their existing memory component encoded by states and weights is too small and not compartmentalized enough to accurately remember facts from the past (RNNs for example, have difficult memorizing and doing tasks like copying).

A memory network consists of a memory $\textbf{m}$ (an array of objects indexed by $\textbf{m}_{i}$ and four potentially learned components:

  • Input feature map $I$ - feature representation of the data input.
  • Generalization $G$ - updates old memories given the new input.
  • Output feature map $O$ - produces new feature map given $I$ and $G$.
  • Response $R$ - converts output into the desired response.

Given an input $x$ (e.g., an input character, word or sentence depending on the granularity chosen, an image or an audio signal) the flow of the model is as follows:

  1. Convert $x$ to an internal feature representation $I\left(x\right)$.
  2. Update memories $m_{i}$ given the new input: $m_{i} = G\left(m_{i}, I\left(x\right), m\right)$, $\forall{i}$.
  3. Compute output features $o$ given the new input and the memory: $o = O\left(I\left(x\right), m\right)$.
  4. Finally, decode output features $o$ to give the final response: $r = R\left(o\right)$.

This process is applied at both train and test time, if there is a distinction between such phases, that is, memories are also stored at test time, but the model parameters of $I$, $G$, $O$ and $R$ are not updated. Memory networks cover a wide class of possible implementations. The components $I$, $G$, $O$ and $R$ can potentially use any existing ideas from the machine learning literature.

Image Source: Adrian Colyer

Source: Memory Networks

Latest Papers

PAPER DATE
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Object Guided External Memory Network for Video Object Detection
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YNU\_DYX at SemEval-2019 Task 9: A Stacked BiLSTM for Suggestion Mining Classification
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Going From Image to Video Saliency: Augmenting Image Salience With Dynamic Attentional Push
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Working Memory Networks: Augmenting Memory Networks with a Relational Reasoning Module
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A Memory Network Approach for Story-based Temporal Summarization of 360° Videos
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A Taxonomy for Neural Memory Networks
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k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks
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Automatic Stance Detection Using End-to-End Memory Networks
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Motion-Appearance Co-Memory Networks for Video Question Answering
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Learning Dynamic Memory Networks for Object Tracking
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How Images Inspire Poems: Generating Classical Chinese Poetry from Images with Memory Networks
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Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks
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Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning
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Graph Memory Networks for Molecular Activity Prediction
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Long-term Multi-granularity Deep Framework for Driver Drowsiness Detection
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Contextual memory bandit for pro-active dialog engagement
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Attentive Memory Networks: Efficient Machine Reading for Conversational Search
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IQA: Visual Question Answering in Interactive Environments
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Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks
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Model-free prediction of noisy chaotic time series by deep learning
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A Read-Write Memory Network for Movie Story Understanding
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Integrating Order Information and Event Relation for Script Event Prediction
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Capturing User and Product Information for Document Level Sentiment Analysis with Deep Memory Network
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Chinese Zero Pronoun Resolution with Deep Memory Network
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End-to-end Learning for Short Text Expansion
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Long-Short Range Context Neural Networks for Language Modeling
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Unified Neural Architecture for Drug, Disease and Clinical Entity Recognition
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MemNet: A Persistent Memory Network for Image Restoration
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Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
Yuan YuanXiaodan LiangXiaolong WangDit-Yan YeungAbhinav Gupta
2017-08-02
Towards Harnessing Memory Networks for Coreference Resolution
Joe CheriPushpak Bhattacharyya
2017-08-01
MEMEN: Multi-layer Embedding with Memory Networks for Machine Comprehension
Boyuan PanHao LiZhou ZhaoBin CaoDeng CaiXiaofei He
2017-07-28
Visual Question Answering with Memory-Augmented Networks
Chao MaChunhua ShenAnthony DickQi WuPeng WangAnton van den HengelIan Reid
2017-07-17
Long-Term Memory Networks for Question Answering
Fenglong MaRadha ChittaSaurabh KatariaJing ZhouPalghat RameshTong SunJing Gao
2017-07-06
A Deep Neural Architecture for Sentence-level Sentiment Classification in Twitter Social Networking
| Huy NguyenMinh-Le Nguyen
2017-06-25
Short-Term Forecasting of Passenger Demand under On-Demand Ride Services: A Spatio-Temporal Deep Learning Approach
Jintao KeHongyu ZhengHai YangXiqunChen
2017-06-20
Adversarial Feature Matching for Text Generation
Yizhe ZhangZhe GanKai FanZhi ChenRicardo HenaoDinghan ShenLawrence Carin
2017-06-12
Wikipedia Vandal Early Detection: from User Behavior to User Embedding
Shuhan YuanPanpan ZhengXintao WuYang Xiang
2017-06-03
Non-Markovian Control with Gated End-to-End Memory Policy Networks
Julien PerezTomi Silander
2017-05-31
Attend to You: Personalized Image Captioning with Context Sequence Memory Networks
| Cesc Chunseong ParkByeongchang KimGunhee Kim
2017-04-21
Spatial Memory for Context Reasoning in Object Detection
| Xinlei ChenAbhinav Gupta
2017-04-13
Tree Memory Networks for Modelling Long-term Temporal Dependencies
Tharindu FernandoSimon DenmanAaron McFadyenSridha SridharanClinton Fookes
2017-03-12
Ask Me Even More: Dynamic Memory Tensor Networks (Extended Model)
| Govardana Sachithanandam RamachandranAjay Sohmshetty
2017-03-11
End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks
Min-je ChoiSehun JeongHakjoo OhJaegul Choo
2017-03-07
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data
| Jiaxuan YouXiaocheng LiMelvin LowDavid LobellStefano Ermon
2017-02-12
Concurrent Activity Recognition with Multimodal CNN-LSTM Structure
Xinyu LiYanyi ZhangJianyu ZhangShuhong ChenIvan MarsicRichard A. FarnethRandall S. Burd
2017-02-06
Visual Dialog
| Abhishek DasSatwik KotturKhushi GuptaAvi SinghDeshraj YadavJosé M. F. MouraDevi ParikhDhruv Batra
2016-11-26
Instance-aware Image and Sentence Matching with Selective Multimodal LSTM
Yan HuangWei WangLiang Wang
2016-11-17
AC-BLSTM: Asymmetric Convolutional Bidirectional LSTM Networks for Text Classification
| Depeng LiangYongdong Zhang
2016-11-07
Truth Discovery with Memory Network
Luyang LiBing QinWenjing RenTing Liu
2016-11-07
Gated End-to-End Memory Networks
| Julien PerezFei Liu
2016-10-13
Knowledge Representation via Joint Learning of Sequential Text and Knowledge Graphs
Jiawei WuRuobing XieZhiyuan LiuMaosong Sun
2016-09-22
Dialog state tracking, a machine reading approach using Memory Network
Julien PerezFei Liu
2016-06-13
Aspect Level Sentiment Classification with Deep Memory Network
| Duyu TangBing QinTing Liu
2016-05-28
Dynamic Memory Networks for Visual and Textual Question Answering
| Caiming XiongStephen MerityRichard Socher
2016-03-04
Long Short-Term Memory-Networks for Machine Reading
| Jianpeng ChengLi DongMirella Lapata
2016-01-25
Recurrent Memory Networks for Language Modeling
| Ke TranArianna BisazzaChristof Monz
2016-01-06
Skip-Thought Memory Networks
Ethan Caballero
2015-11-19
Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering
Huijuan XuKate Saenko
2015-11-17
Memory Networks
| Jason WestonSumit ChopraAntoine Bordes
2014-10-15

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