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
On Lifting the Gibbs Sampling Algorithm—0
Slice Normalized Dynamic Markov Logic Networks—0
Search Space Properties for Learning a Class of Constraint-based Grammars—0
A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories—0
Reading The Web with Learned Syntactic-Semantic Inference Rules—0
Learning to ``Read Between the Lines'' using Bayesian Logic Programs—0
Adding Distributional Semantics to Knowledge Base Entities through Web-scale Entity Linking—0
kLog: A Language for Logical and Relational Learning with Kernels—0
A Three-Way Model for Collective Learning on Multi-Relational Data—0
Efficient Relational Learning with Hidden Variable Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified