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 311–320 of 483 papers

TitleStatusHype
A Boosting Approach to Learning Graph Representations—0
Abstraction and Relational learning—0
A Complete Characterization of Projectivity for Statistical Relational Models—0
A Concept-Centered Hypertext Approach to Case-Based Retrieval—0
A Critical Review of Inductive Logic Programming Techniques for Explainable AI—0
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations—0
Adaptive Convolution for Multi-Relational Learning—0
Adding Distributional Semantics to Knowledge Base Entities through Web-scale Entity Linking—0
Agent-Centric Representations for Multi-Agent Reinforcement Learning—0
A Learning Algorithm for Relational Logistic Regression: Preliminary Results—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified