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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 391–400 of 483 papers

TitleStatusHype
Scalable Label Propagation for Multi-relational Learning on the Tensor Product of GraphsCode0
TransRev: Modeling Reviews as Translations from Users to Items—0
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning—0
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations—0
Recurrent Relational Networks for complex relational reasoningCode0
RelNN: A Deep Neural Model for Relational LearningCode0
Broadcasting Convolutional Network for Visual Relational Reasoning—0
Temporal Relational Reasoning in VideosCode0
Recurrent Relational NetworksCode0
Tensor Decompositions for Modeling Inverse Dynamics—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified