David Muhr

According to our database, David Muhr authored at least 10 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

A Probabilistic Transformation of Distance-Based Outliers.

David Muhr, Michael Affenzeller, Josef Küng

Mach. Learn. Knowl. Extr., June, 2023

Probabilistic Distance-Based Outlier Detection.

David Muhr, Michael Affenzeller, Josef Küng

CoRR, 2023

Implicit Directed Acyclic Graphs (DAGs) for Parallel Outlier/Anomaly Detection Ensembles.

David Muhr, Michael Affenzeller, Josef Küng

Proceedings of the Artificial Intelligence Applications and Innovations, 2023

2022

OutlierDetection.jl: A modular outlier detection ecosystem for the Julia programming language.

David Muhr, Michael Affenzeller, Anthony D. Blaom

CoRR, 2022

Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional Spaces.

David Muhr, Michael Affenzeller

Proceedings of the Artificial Intelligence Applications and Innovations, 2022

Outlier/Anomaly Detection of Univariate Time Series: A Dataset Collection and Benchmark.

David Muhr, Michael Affenzeller

Proceedings of the Big Data Analytics and Knowledge Discovery, 2022

2021

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing.

Shailesh Tripathi, David Muhr, Manuel Brunner, Herbert Jodlbauer, Matthias Dehmer, Frank Emmert-Streib

Frontiers Artif. Intell., 2021

Little data is often enough for distance-based outlier detection.

David Muhr, Michael Affenzeller

Proceedings of the 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2022), Virtual Event / Upper Austria University of Applied Sciences - Hagenberg Campus, 2021

2020

Large scale predictability analysis of process variables from injection molding machines.

Shailesh Tripathi, Christian Mittermayr, David Muhr, Herbert Jodlbauer

Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020), 2020

An adaptive machine learning methodology to determine manufacturing process parameters for each part.

David Muhr, Shailesh Tripathi, Herbert Jodlbauer

Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020), 2020