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 71–80 of 483 papers

TitleStatusHype
Better Set Representations For Relational ReasoningCode1
Self-Attentive Associative MemoryCode1
Generative Adversarial Zero-Shot Relational Learning for Knowledge GraphsCode1
Quantum Embedding of Knowledge for ReasoningCode1
Inductive Relation Prediction by Subgraph ReasoningCode1
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image InterpretationCode1
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from TextCode1
Neural Logic MachinesCode1
Fast Graph Representation Learning with PyTorch GeometricCode1
Relational inductive biases, deep learning, and graph networksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified