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 161–170 of 483 papers

TitleStatusHype
Continual Reasoning: Non-Monotonic Reasoning in Neurosymbolic AI using Continual Learning—0
Cluster Flow: how a hierarchical clustering layer make allows deep-NNs more resilient to hacking, more human-like and easily implements relational reasoning—0
Retrieval-based Knowledge Augmented Vision Language Pre-training—0
Geometric Relational Embeddings: A Survey—0
Medical Image Analysis using Deep Relational Learning—0
Enhancing Embedding Representations of Biomedical Data using Logic Knowledge—0
Local Region Perception and Relationship Learning Combined with Feature Fusion for Facial Action Unit Detection—0
Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational ReasoningCode0
Weighted First Order Model Counting with Directed Acyclic Graph Axioms—0
Principled and Efficient Motif Finding for Structure Learning of Lifted Graphical ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified