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

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Showing 371–380 of 483 papers

TitleStatusHype
Graph-Based Global Reasoning NetworksCode0
Efficient Coarse-to-Fine Non-Local Module for the Detection of Small Objects—0
A Concept-Centered Hypertext Approach to Case-Based Retrieval—0
Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations—0
Compositional Language Understanding with Text-based Relational ReasoningCode0
Multi-layer Relation Networks—0
Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data—0
Dilated DenseNets for Relational Reasoning—0
SARN: Relational Reasoning through Sequential Attention—0
Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified