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 471–480 of 483 papers

TitleStatusHype
R5: Rule Discovery with Reinforced and Recurrent Relational ReasoningCode0
Adversarial Sets for Regularising Neural Link PredictorsCode0
Associative TransformerCode0
Scalable Label Propagation for Multi-relational Learning on the Tensor Product of GraphsCode0
Complementary Structure-Learning Neural Networks for Relational ReasoningCode0
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
Show:102550
← PrevPage 48 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified