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 371–380 of 483 papers

TitleStatusHype
Decoupling Mixture-of-Graphs: Unseen Relational Learning for Knowledge Graph Completion by Fusing Ontology and Textual Experts—0
Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation—0
Deep Inductive Logic Reasoning for Multi-Hop Reading Comprehension—0
Deep Learning for Ontology Reasoning—0
Deep reinforcement learning with relational inductive biases—0
Deep Semantic Abstractions of Everyday Human Activities: On Commonsense Representations of Human Interactions—0
Deep Sets for Generalization in RL—0
Demystifying Relational Latent Representations—0
Desk Organization: Effect of Multimodal Inputs on Spatial Relational Learning—0
DEVICE: DEpth and VIsual ConcEpts Aware Transformer for TextCaps—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified