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DeepNLP-Study

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Hyunho Cho edited this page Jan 11, 2018 · 3 revisions

Welcome to the DeepNLP-Study wiki!

Wiki pages Pages 44

Home
[PAPERS REVIEWED]
[Q&A for CMU Neural Networks for NLP 2018]
[SCHEDULE & CHECK UP]
[스터디 세부 계획 (2018년 1~2월)]
A Hierarchical Latent Variable Encoder Decoder Model for Generating Dialogues
A Hierarchical Recurrent Encoder Decoder for Generative Context Aware Query Suggestion
A Persona Based Neural Conversation Model
Attend to You: Personalized Image Captioning with Context Sequence Memory Networks
Attention Is All You Need 논문리뷰
Bidirectional Attention Flow for Machine Comprehension(2016)
ByteNet : Neural Machine Translation in Linear Time
Character Aware Neural Language Model(2016)
Character level Convolutional Networks for Text Classification
Character Word LSTM Language Models paper review
Convolutional Neural Networks for Sentence Classification
Day 01 Summary 180104
Day 02 Paper Review: ResNet
Depthwise Separable Convolutions for Neural Machine Translation
Effective Approaches to Attention based Neural Machine Translation
End to end Sequence Labeling via Bi directional LSTM CNNs CRF
Identity Mappings in Deep Residual Nets
Improved Semantic RepresentationsFrom Tree Structured LongShort TermMemory Networks
Key Value Memory Networks for Directly Reading Documents(2017)
Learned in Translation: Contextualized Word Vectors(2017)
Learning End To End Goal Oriented Dialog
Learning to Remember Rare Events
Memory Networks 논문 리뷰
MILABOT : A Deep Reinforcement Learning Chatbot
Neural Conversational Model
NMT by Jointly Learning to Align and Translate
QRNN
Residual Networks Behave Like Ensembles of Relatively Shallow Networks
Review of a lecture 2 A Diversity Promoting Objective Function for Neural Conversation Models
Review of a paper : A Convolutional Neural Network for Modeling Sentences
Sensitivity Analysis of CNN for Sentence Classification
Sequence to Sequence Learning with Neural Nerworks
Show and Tell: A Neural Image Caption Generator 논문 리뷰
Show Attend and Tell
TCML : Temporal Convolution based Meta Learner
Text Understanding from Scratch
The Ubuntu Dialogue Corpus
TRAINING RNNs AS FAST AS CNN
Very Deep CNN(VDCNN) for NLP

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