Design and analysis of PKM robots for ultra fast blanking. - Nathan Baumli; Rajendra Patel; Michael Platzer; Roger Pons; Ramon Casanelles; Daniel Wappling; Xiaolong Feng (ISR, 2013)

New robot concept for ultra high performance press tending robot system. - Michael Platzer; Xiaolong Feng; Daniel Wappling; Nathan Baumli; Rajendra Patel; Roger Pons; Ramon Casanelles; Jakob Westrom (ISR, 2013)

Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity. - Michael Platzer; Thomas Reutterer (Mark. Sci., 2016)

CPS/IoT Ecosystem: A Platform for Research and Education. - Haris Isakovic; Denise Ratasich; Christian Hirsch; Michael Platzer; Bernhard Wally; Thomas Rausch; Dejan Nickovic; Willibald Krenn; Gerti Kappel; Schahram Dustdar; Radu Grosu (CyPhy/WESE, 2018)

Adaptive Fault Detection Exploiting Redundancy with Uncertainties in Space and Time. - Denise Ratasich; Michael Platzer; Radu Grosu; Ezio Bartocci (SASO, 2019)

A Real-Time Application with Fully Predictable Task Timing. - Michael Platzer; Peter P. Puschner (ISORC, 2020)

An Instruction Filter for Time-Predictable Code Execution on Standard Processors. - Michael Platzer; Peter P. Puschner (SAFECOMP Workshops, 2020)

Vicuna: A Timing-Predictable RISC-V Vector Coprocessor for Scalable Parallel Computation. - Michael Platzer; Peter P. Puschner (ECRTS, 2021)

A Processor Extension for Time-Predictable Code Execution. - Michael Platzer; Peter P. Puschner (ISORC, 2021)

Holdout-Based Fidelity and Privacy Assessment of Mixed-Type Synthetic Data. - Michael Platzer; Thomas Reutterer (CoRR, 2021)

Holdout-Based Empirical Assessment of Mixed-Type Synthetic Data. - Michael Platzer; Thomas Reutterer (Frontiers Big Data, 2021)

AI-based Re-identification of Behavioral Clickstream Data. - Stefan Vamosi; Michael Platzer; Thomas Reutterer (CoRR, 2022)

Rule-adhering synthetic data - the lingua franca of learning. - Michael Platzer; Ivona Krchova (CoRR, 2022)

A deep recurrent neural network approach to learn sequence similarities for user-identification. - Stefan Vamosi; Thomas Reutterer; Michael Platzer (Decis. Support Syst., 2022)

Strong statistical parity through fair synthetic data. - Ivona Krchova; Michael Platzer; Paul Tiwald (CoRR, 2023)

TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data. - Paul Tiwald; Ivona Krchova; Andrey Sidorenko; Mariana Vargas Vieyra; Mario Scriminaci; Michael Platzer (CoRR, 2025)

Benchmarking Synthetic Tabular Data: A Multi-Dimensional Evaluation Framework. - Andrey Sidorenko; Michael Platzer; Mario Scriminaci; Paul Tiwald (CoRR, 2025)

Improving Predictions on Highly Unbalanced Data Using Open Source Synthetic Data Upsampling. - Ivona Krchova; Michael Platzer; Paul Tiwald (CoRR, 2025)