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 301–310 of 483 papers

TitleStatusHype
Stochastic And-Or Grammars: A Unified Framework and Logic Perspective—0
Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls—0
StrokeNet: Stroke Assisted and Hierarchical Graph Reasoning Networks—0
Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors—0
Structural Relational Reasoning of Point Clouds—0
Structural Representations for Learning Relations between Pairs of Texts—0
Subverting machines, fluctuating identities: Re-learning human categorization—0
Swift Markov Logic for Probabilistic Reasoning on Knowledge Graphs—0
Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring—0
Symbolic Logic meets Machine Learning: A Brief Survey in Infinite Domains—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified