Relation
1084 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Libraries
Use these libraries to find Relation models and implementationsMost implemented papers
Learning to Compare: Relation Network for Few-Shot Learning
floodsung/LearningToCompare_FSL
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CVPR 2018
Once trained, a RN is able to classify images of new classes by computing relation scores between query images and the few examples of each new class without further updating the network.
Matching the Blanks: Distributional Similarity for Relation Learning
plkmo/BERT-Relation-Extraction
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ACL 2019
General purpose relation extractors, which can model arbitrary relations, are a core aspiration in information extraction.
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
DeepGraphLearning/KnowledgeGraphEmbedding
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ICLR 2019
We study the problem of learning representations of entities and relations in knowledge graphs for predicting missing links.
Inductive Relation Prediction by Subgraph Reasoning
The dominant paradigm for relation prediction in knowledge graphs involves learning and operating on latent representations (i. e., embeddings) of entities and relations.
OCNet: Object Context Network for Scene Parsing
PkuRainBow/OCNet
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To capture richer context information, we further combine our interlaced sparse self-attention scheme with the conventional multi-scale context schemes including pyramid pooling~\citep{zhao2017pyramid} and atrous spatial pyramid pooling~\citep{chen2018deeplab}.
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Spatial-temporal graph modeling is an important task to analyze the spatial relations and temporal trends of components in a system.
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
shehzaadzd/MINERVA
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ICLR 2018
Knowledge bases (KB), both automatically and manually constructed, are often incomplete --- many valid facts can be inferred from the KB by synthesizing existing information.
Neural Motifs: Scene Graph Parsing with Global Context
rowanz/neural-motifs
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CVPR 2018
We then introduce Stacked Motif Networks, a new architecture designed to capture higher order motifs in scene graphs that further improves over our strong baseline by an average 7. 1% relative gain.
Relation Networks for Object Detection
msracver/Relation-Networks-for-Object-Detection
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CVPR 2018
Although it is well believed for years that modeling relations between objects would help object recognition, there has not been evidence that the idea is working in the deep learning era.
Joint entity recognition and relation extraction as a multi-head selection problem
bekou/multihead_joint_entity_relation_extraction
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State-of-the-art models for joint entity recognition and relation extraction strongly rely on external natural language processing (NLP) tools such as POS (part-of-speech) taggers and dependency parsers.
