Design of an Energy Efficient Voltage-to-Time Converter with Rectified Linear Unit Characteristics for Artificial Neural Networks. - Jakob Finkbeiner; Raphael Nägele; Markus Grözing; Manfred Berroth (NEWCAS, 2022)

Design of an Energy Efficient Analog Two-Quadrant Multiplier Cell Operating in Weak Inversion. - Raphael Nägele; Jakob Finkbeiner; Markus Grözing; Manfred Berroth (NEWCAS, 2022)

Time-Interleaved Switched Emitter Followers to Extend Front-End Sampling Rates to up to 200 GS/s. - Philipp Thomas; Jakob Finkbeiner; Markus Grözing; Manfred Berroth (IEEE J. Solid State Circuits, 2022)

Analog Multiply-Accumulate Cell With Multi-Bit Resolution for All-Analog AI Inference Accelerators. - Raphael Nägele; Jakob Finkbeiner; Valentin Stadtlander; Markus Grözing; Manfred Berroth (IEEE Trans. Circuits Syst. I Regul. Pap., 2023)

Characterization of a Femtojoule Voltage-to-Time Converter with Rectified Linear Unit Characteristic for Analog Neural Network Inference Accelerators. - Jakob Finkbeiner; Raphael Nägele; Markus Grözing; Manfred Berroth; Georg Rademacher (AICAS, 2024)

Characterization of an Analog MAC Cell with Multi-Bit Resolution for AI Inference Accelerators. - Raphael Nägele; Jakob Finkbeiner; Markus Grözing; Manfred Berroth; Georg Rademacher (AICAS, 2024)