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 441–450 of 483 papers

TitleStatusHype
Lifted Symmetry Detection and Breaking for MAP Inference—0
The CTU Prague Relational Learning Repository—0
Holographic Embeddings of Knowledge GraphsCode0
Lifted Relational Neural Networks—0
Schema Independent Relational Learning—0
FactorBase: SQL for Learning A Multi-Relational Graphical Model—0
SQL for SRL: Structure Learning Inside a Database System—0
Structural Representations for Learning Relations between Pairs of Texts—0
Learning Relational Features with Backward Random Walks—0
Matrix and Tensor Factorization Methods for Natural Language Processing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified