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 231–240 of 483 papers

TitleStatusHype
Learning Reasoning Patterns for Relational Triple Extraction with Mutual Generation of Text and Graph—0
Finding ReMO (Related Memory Object): A Simple Neural Architecture for Text based Reasoning—0
Learning Relational Features with Backward Random Walks—0
Learning Relational Representations with Auto-encoding Logic Programs—0
Relational Reasoning Networks—0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
Financial Risk Assessment via Long-term Payment Behavior Sequence Folding—0
Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation—0
Learning to Coarsen Graphs with Graph Neural Networks—0
Lifted Symmetry Detection and Breaking for MAP Inference—0
Show:102550
← PrevPage 24 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified