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 341–350 of 483 papers

TitleStatusHype
Cognitive Knowledge Graph Reasoning for One-shot Relational LearningCode0
WikiDataSets: Standardized sub-graphs from WikidataCode0
Relational Reasoning using Prior Knowledge for Visual Captioning—0
Composition of Sentence Embeddings: Lessons from Statistical Relational Learning—0
Adaptive Convolution for Multi-Relational Learning—0
Structural Relational Reasoning of Point Clouds—0
Neural Markov Logic Networks—0
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge GraphsCode0
An Explicitly Relational Neural Network ArchitectureCode0
Neural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified