Search Results for author: Daria Stepanova

Found 6 papers, 0 papers with code

Neuro-Symbolic Ontology-Mediated Query Answering

no code implementations29 Sep 2021 Medina Andresel, Daria Stepanova, Trung-Kien Tran, Csaba Domokos, Pasquale Minervini

Recently, low-dimensional vector space representations of Knowledge Graphs (KGs) have been applied to find answers to logical queries over incomplete KGs.

Data Augmentation Knowledge Graphs

On Event-Driven Knowledge Graph Completion in Digital Factories

no code implementations8 Sep 2021 Martin Ringsquandl, Evgeny Kharlamov, Daria Stepanova, Steffen Lamparter, Raffaello Lepratti, Ian Horrocks, Peer Kröger

Smooth operation of such factories requires that the machines and engineering personnel that conduct their monitoring and diagnostics share a detailed common industrial knowledge about the factory, e. g., in the form of knowledge graphs.

Knowledge Graph Completion

A Neural-symbolic Approach for Ontology-mediated Query Answering

no code implementations26 Jun 2021 Medina Andresel, Csaba Domokos, Daria Stepanova, Trung-Kien Tran

The experimental results demonstrate the effectiveness of our training strategies and the new loss function, i. e., our method significantly outperforms the baseline in the settings that require both inductive and deductive reasoning.

Data Augmentation Knowledge Graphs

A method to coarse-grain multi-agent stochastic systems with regions of multistability

no code implementations7 May 2021 Daria Stepanova, Helen M. Byrne, Philip K. Maini, Tomás Alarcón

Here we use large deviation theory to decrease the computational cost of a spatially-extended multi-agent stochastic system with a region of multi-stability by coarse-graining it to a continuous time Markov chain on the state space of stable steady states of the original system.

Differentiable learning of numerical rules in knowledge graphs

no code implementations ICLR 2020 Po-Wei Wang, Daria Stepanova, Csaba Domokos, J. Zico Kolter

Rules over a knowledge graph (KG) capture interpretable patterns in data and can be used for KG cleaning and completion.

Knowledge Graphs

Hybrid ASP-based Approach to Pattern Mining

no code implementations22 Aug 2018 Sergey Paramonov, Daria Stepanova, Pauli Miettinen

We present a hybrid approach for itemset, sequence and graph mining which exploits dedicated highly optimized mining systems to detect frequent patterns and then filters the results using declarative ASP.

Graph Mining

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