Search Results for author:
Found 9 papers, 1 papers with code
Computational modelling of angiogenesis: The importance of cell rearrangements during vascular growth
This review of the theoretical modelling of angiogenesis is the first to focus on the phenomenon of cell mixing during early sprouting.
Contextual Reasoning for Scene Generation (Technical Report)
In this paper, we show how to apply our theoretical work to real autonomous-vehicle scene data.
Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling
We study the application of Answer-Set Programming (ASP) to solve this problem.
Neuro-Symbolic Ontology-Mediated Query Answering
Recently, low-dimensional vector space representations of Knowledge Graphs (KGs) have been applied to find answers to logical queries over incomplete KGs.
On Event-Driven Knowledge Graph Completion in Digital Factories
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.
Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs
Current methods for embedding-based query answering over incomplete Knowledge Graphs (KGs) only focus on inductive reasoning, i. e., predicting answers by learning patterns from the data, and lack the complementary ability to do deductive reasoning, which requires the application of domain knowledge to infer further information.
A method to coarse-grain multi-agent stochastic systems with regions of multistability
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
Rules over a knowledge graph (KG) capture interpretable patterns in data and can be used for KG cleaning and completion.
Hybrid ASP-based Approach to Pattern Mining
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.
