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 351–360 of 483 papers

TitleStatusHype
Object-Oriented Model Learning through Multi-Level Abstraction—0
Neural Logic MachinesCode1
Object-Oriented Dynamics Learning through Multi-Level AbstractionCode0
A Relation-Augmented Fully Convolutional Network for Semantic Segmentation in Aerial Scenes—0
Relational Reasoning Network (RRN) for Anatomical Landmarking—0
Composition of Sentence Embeddings:Lessons from Statistical Relational Learning—0
Learning Relational Representations with Auto-encoding Logic Programs—0
Fast Graph Representation Learning with PyTorch GeometricCode1
Multi-Label Network Classification via Weighted Personalized Factorizations—0
MUREL: Multimodal Relational Reasoning for Visual Question AnsweringCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified