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 476–483 of 483 papers

TitleStatusHype
WikiDataSets: Standardized sub-graphs from WikidataCode0
Graph Neural Networks with Generated Parameters for Relation ExtractionCode0
CommonGen: A Constrained Text Generation Challenge for Generative Commonsense ReasoningCode0
Graph Based Relational Features for Collective ClassificationCode0
Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational ReasoningCode0
Recurrent Relational NetworksCode0
Recurrent Relational Networks for complex relational reasoningCode0
TGraphX: Tensor-Aware Graph Neural Network for Multi-Dimensional Feature LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified