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 376–400 of 483 papers

TitleStatusHype
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
Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement—0
Dilated DenseNets for Relational Reasoning—0
Discriminative Gaifman Models—0
Distilling Structured Knowledge for Text-Based Relational Reasoning—0
Distributed Associative Memory Network with Association Reinforcing Loss—0
Does Entity Abstraction Help Generative Transformers Reason?—0
Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation—0
Domain-Liftability of Relational Marginal Polytopes—0
Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data—0
Efficient Coarse-to-Fine Non-Local Module for the Detection of Small Objects—0
Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic—0
Efficient Relational Learning with Hidden Variable Detection—0
End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning—0
Enhancing Embedding Representations of Biomedical Data using Logic Knowledge—0
Ensemble Relational Learning based on Selective Propositionalization—0
Estimating Aggregate Properties In Relational Networks With Unobserved Data—0
Evaluating the Progress of Deep Learning for Visual Relational Concepts—0
EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning—0
EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction—0
Explicit Relational Reasoning Network for Scene Text Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified