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 426–450 of 483 papers

TitleStatusHype
Multiple protein feature prediction with statistical relational learningβ€”0
Column Networks for Collective ClassificationCode0
OSL𝛼: Online Structure Learning Using Background Knowledge AxiomatizationCode1
Relational Similarity Machinesβ€”0
Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Textβ€”0
Application of Statistical Relational Learning to Hybrid Recommendation Systemsβ€”0
On the Semantic Relationship between Probabilistic Soft Logic and Markov Logicβ€”0
A Learning Algorithm for Relational Logistic Regression: Preliminary Resultsβ€”0
Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representationβ€”0
Complex Embeddings for Simple Link PredictionCode2
ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Foraβ€”0
Scalable Statistical Relational Learning for NLPβ€”0
Cross-Graph Learning of Multi-Relational Associationsβ€”0
Multi-Relational Learning at Scale with ADMMβ€”0
Regularized Orthogonal Tensor Decompositions for Multi-Relational Learningβ€”0
Lifted Symmetry Detection and Breaking for MAP Inferenceβ€”0
The CTU Prague Relational Learning Repositoryβ€”0
Holographic Embeddings of Knowledge GraphsCode0
Lifted Relational Neural Networksβ€”0
Schema Independent Relational Learningβ€”0
FactorBase: SQL for Learning A Multi-Relational Graphical Modelβ€”0
SQL for SRL: Structure Learning Inside a Database Systemβ€”0
Matrix and Tensor Factorization Methods for Natural Language Processingβ€”0
Joint Information Extraction and Reasoning: A Scalable Statistical Relational Learning Approachβ€”0
Learning Relational Features with Backward Random Walksβ€”0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99β€”Unverified