SOTAVerified

Relational Reasoning

The goal of Relational Reasoning is to figure out the relationships among different entities, such as image pixels, words or sentences, human skeletons or interactive moving agents.

Source: Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

Papers

Showing 391400 of 483 papers

TitleStatusHype
Working Memory Networks: Augmenting Memory Networks with a Relational Reasoning Module0
VC-Dimension Based Generalization Bounds for Relational Learning0
Scalable Label Propagation for Multi-relational Learning on the Tensor Product of GraphsCode0
TransRev: Modeling Reviews as Translations from Users to Items0
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning0
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations0
Recurrent Relational Networks for complex relational reasoningCode0
Broadcasting Convolutional Network for Visual Relational Reasoning0
RelNN: A Deep Neural Model for Relational LearningCode0
Temporal Relational Reasoning in VideosCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99Unverified