FINN-T: Compiling Custom Dataflow Accelerators for Quantized Transformers
C. Berganski, F. Jentzsch, M. Platzner, M. Kuhmichel, H. Giefers, in: 2024.

Flexible Industrial Analytics on Reconfigurable Systems-On-Chip
A. Boschmann, L. Clausing, F. Jentzsch, H. Ghasemzadeh Mohammadi, M. Platzner, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 225–236.

Hardware-Aware AutoML for Exploration of Custom FPGA Accelerators for RadioML
F. Jentzsch, in: 2023 33rd International Conference on Field-Programmable Logic and Applications (FPL), IEEE, 2023.

RadioML Meets FINN: Enabling Future RF Applications With FPGA Streaming Architectures
F. Jentzsch, Y. Umuroglu, A. Pappalardo, M. Blott, M. Platzner, IEEE Micro 42 (2022) 125–133.

FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial Analytics
H. Ghasemzadeh Mohammadi, F. Jentzsch, M. Kuschel, R. Arshad, S. Rautmare, S. Manjunatha, M. Platzner, A. Boschmann, D. Schollbach, in:  Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Springer, 2021.