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 251–260 of 483 papers

TitleStatusHype
Propagating Over Phrase Relations for One-Stage Visual Grounding—0
Relational Algorithms for k-means Clustering—0
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational LearningCode1
Distributed Associative Memory Network with Memory Refreshing LossCode0
Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs—0
Graph-Based Social Relation ReasoningCode1
Beyond Graph Neural Networks with Lifted Relational Neural NetworksCode1
Learning Reasoning Strategies in End-to-End Differentiable ProvingCode1
Relational-Grid-World: A Novel Relational Reasoning Environment and An Agent Model for Relational Information Extraction—0
Recurrent Relational Memory Network for Unsupervised Image Captioning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified