3 citations · 3 across the 5 of their papers we have counts for
5 papers
Variables are a Curse in Software Vulnerability Prediction
Jinghua Groppe, Sven Groppe, Ralf Möller
Deep learning-based approaches for software vulnerability prediction currently mainly rely on the original text of software code as the feature of nodes in the graph of code and th…
Improved Convergence Speed of Fully Symmetric Learning Rules for Principal Component Analysis
Ralf Möller
Fully symmetric learning rules for principal component analysis can be derived from a novel objective function suggested in our previous work. We observed that these learning rules…
Answering Hindsight Queries with Lifted Dynamic Junction Trees
Marcel Gehrke, Tanya Braun, Ralf Möller
The lifted dynamic junction tree algorithm (LDJT) efficiently answers filtering and prediction queries for probabilistic relational temporal models by building and then reusing a f…
Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm
Marcel Gehrke, Tanya Braun, Ralf Möller
The lifted dynamic junction tree algorithm (LDJT) efficiently answers filtering and prediction queries for probabilistic relational temporal models by building and then reusing a f…
Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm
Tanya Braun, Ralf Möller
Standard approaches for inference in probabilistic formalisms with first-order constructs include lifted variable elimination (LVE) for single queries as well as first-order knowle…