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 381–390 of 483 papers

TitleStatusHype
The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR—0
Mapping Natural Language Commands to Web ElementsCode0
One-Shot Relational Learning for Knowledge GraphsCode0
LinkNBed: Multi-Graph Representation Learning with Entity Linkage—0
Learning Probabilistic Logic Programs in Continuous Domains—0
A Comparative Study of Distributional and Symbolic Paradigms for Relational LearningCode0
Modularity Matters: Learning Invariant Relational Reasoning Tasks—0
Relational Deep Reinforcement LearningCode0
Relational recurrent neural networksCode0
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified