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

Showing 401425 of 483 papers

TitleStatusHype
Recurrent Relational NetworksCode0
Tensor Decompositions for Modeling Inverse Dynamics0
Mandolin: A Knowledge Discovery Framework for the Web of DataCode0
Deep Semantic Abstractions of Everyday Human Activities: On Commonsense Representations of Human Interactions0
Usable & Scalable Learning Over Relational Data With Automatic Language Bias0
On Inductive Abilities of Latent Factor Models for Relational LearningCode0
Character-based recurrent neural networks for morphological relational reasoning0
Multi-task Neural Network for Non-discrete Attribute Prediction in Knowledge Graphs0
KeLP at SemEval-2017 Task 3: Learning Pairwise Patterns in Community Question Answering0
Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks0
Adversarial Sets for Regularising Neural Link PredictorsCode0
Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls0
RelTextRank: An Open Source Framework for Building Relational Syntactic-Semantic Text Pair Representations0
Robust Face Tracking using Multiple Appearance Models and Graph Relational LearningCode0
RelNet: End-to-End Modeling of Entities & Relations0
A simple neural network module for relational reasoningCode0
Deep Learning for Ontology Reasoning0
Logic Tensor Networks for Semantic Image InterpretationCode0
Induction of Interpretable Possibilistic Logic Theories from Relational Data0
Online learnability of Statistical Relational Learning in anomaly detection0
Demystifying Relational Latent Representations0
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge GraphsCode0
Knowledge Graph Completion via Complex Tensor FactorizationCode0
Graph Based Relational Features for Collective ClassificationCode0
Introducing DRAIL -- a Step Towards Declarative Deep Relational Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99Unverified