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 476–483 of 483 papers

TitleStatusHype
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
Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning—0
Ranking relations using analogies in biological and information networks—0
Abstraction and Relational learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified