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 261–270 of 483 papers

TitleStatusHype
Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking—0
Facial Action Unit Detection via Adaptive Attention and Relation—0
SQL for SRL: Structure Learning Inside a Database System—0
Deep Message Passing on Sets—0
Probabilities of the Third Type: Statistical Relational Learning and Reasoning with Relative Frequencies—0
Statistical relational learning and neuro-symbolic AI: what does first-order logic offer?—0
Stochastic And-Or Grammars: A Unified Framework and Logic Perspective—0
Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls—0
StrokeNet: Stroke Assisted and Hierarchical Graph Reasoning Networks—0
Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors—0
Show:102550
← PrevPage 27 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified