David Muhr - researchr alias

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Viewing Publication 1 - 8 from 8

2023

Implicit Directed Acyclic Graphs (DAGs) for Parallel Outlier/Anomaly Detection EnsemblesDavid Muhr, Michael Affenzeller, Josef Küng. ifip12 2023: 3-15 [doi]

A Probabilistic Transformation of Distance-Based OutliersDavid Muhr, Michael Affenzeller, Josef Küng. make, 5(3):782-802, June 2023. [doi]

2022

Outlier/Anomaly Detection of Univariate Time Series: A Dataset Collection and BenchmarkDavid Muhr, Michael Affenzeller. dawak 2022: 163-169 [doi]

Hybrid (CPU/GPU) Exact Nearest Neighbors Search in High-Dimensional SpacesDavid Muhr, Michael Affenzeller. ifip12 2022: 112-123 [doi]

2021

Little data is often enough for distance-based outlier detectionDavid Muhr, Michael Affenzeller. ism2 2022: 984-992 [doi]

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and ManufacturingShailesh Tripathi, David Muhr, Manuel Brunner, Herbert Jodlbauer, Matthias Dehmer, Frank Emmert-Streib. frai, 4:576892, 2021. [doi]

2020

An adaptive machine learning methodology to determine manufacturing process parameters for each partDavid Muhr, Shailesh Tripathi, Herbert Jodlbauer. ism2 2021: 764-771 [doi]

Large scale predictability analysis of process variables from injection molding machinesShailesh Tripathi, Christian Mittermayr, David Muhr, Herbert Jodlbauer. ism2 2021: 545-560 [doi]

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