A Generic Procedural Generator for Sizing of Analog Integrated Circuits. - Matthias Schweikardt; Yannick Uhlmann; Florian Leber; Jürgen Scheible; Husni M. Habal (PRIME, 2019)

Deep Reinforcement Learning for Analog Circuit Sizing with an Electrical Design Space and Sparse Rewards. - Yannick Uhlmann; Michael Essich; Lennart Bramlage; Jürgen Scheible; Cristóbal Curio (MLCAD, 2022)

Differentiable Neural Network Surrogate Models for gm/ID-based Analog IC Sizing Optimization. - Yannick Uhlmann; Till Moldenhauer; Jürgen Scheible (MLCAD, 2023)

Integrating Multiple Knowledge-based Automation Methodologies into the A/MS IC Design Flow. - Benjamin Prautsch; Ralf Sommer; Jürgen Scheible; Uwe Eichler; Lorenz Renner; Till Moldenhauer; Matthias Schweikardt; Yannick Uhlmann (SMACD, 2024)

An Open-Source Environment for Evaluating Reinforcement Learning Algorithms for Analog IC Floorplanning. - Till Moldenhauer; Yannick Uhlmann; Jürgen Scheible (SMACD, 2025)

Application of the Expert Design Plan Methodology on an Ultra-Low-Power Sensor Frontend. - Lorenz Renner; Ralf Sommer; Yannick Uhlmann (SMACD, 2025)

Sensorless Robust Anomaly Detection of Roller Chain Systems Based on Motor Driver Data and Deep Weighted KNN. - Junyu Qi; Zhuyun Chen 001; Yannick Uhlmann; Gernot Schullerus (IEEE Trans. Instrum. Meas., 2025)

Interactive Visual Performance Space Exploration of Operational Amplifiers with Differentiable Neural Network Surrogate Models. - Yannick Uhlmann; Till Moldenhauer; Jürgen Scheible (ACM Trans. Design Autom. Electr. Syst., 2025)