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 431–440 of 483 papers

TitleStatusHype
Imagine, Reason and Write: Visual Storytelling with Graph Knowledge and Relational Reasoning—0
Important Object Identification with Semi-Supervised Learning for Autonomous Driving—0
Improving Composition of Sentence Embeddings through the Lens of Statistical Relational Learning—0
Improving End-to-End Object Tracking Using Relational Reasoning—0
Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations—0
Improving Skip-Gram based Graph Embeddings via Centrality-Weighted Sampling—0
Improving Scene Graph Classification by Exploiting Knowledge from Texts—0
Incorporating Relational Background Knowledge into Reinforcement Learning via Differentiable Inductive Logic Programming—0
Induction of Interpretable Possibilistic Logic Theories from Relational Data—0
Inductive Logic Boosting—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified