QONNX: Representing Arbitrary-Precision Quantized Neural Networks. - Alessandro Pappalardo; Yaman Umuroglu; Michaela Blott; Jovan Mitrevski; Benjamin Hawks; Nhan Tran; Vladimir Loncar; Sioni Summers; Hendrik Borras; Jules Muhizi; Matthew Trahms; Shih-Chieh Hsu; et al. (CoRR, 2022)

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. - Hendrik Borras; Giuseppe Di Guglielmo; Javier M. Duarte; Nicolò Ghielmetti; Benjamin Hawks; Scott Hauck; Shih-Chieh Hsu; Ryan Kastner; Jason Liang; Andres Meza 001; Jules Muhizi; Tai Nguyen 003; et al. (CoRR, 2022)

Walking Noise: Understanding Implications of Noisy Computations on Classification Tasks. - Hendrik Borras; Bernhard Klein; Holger Fröning (CoRR, 2022)

Walking Noise: On Layer-Specific Robustness of Neural Architectures Against Noisy Computations and Associated Characteristic Learning Dynamics. - Hendrik Borras; Bernhard Klein; Holger Fröning (ECML/PKDD (4), 2024)

On Hardening DNNs against Noisy Computations. - Xiao Wang; Hendrik Borras; Bernhard Klein; Holger Fröning (CoRR, 2025)

Variance-Aware Noisy Training: Hardening DNNs against Unstable Analog Computations. - Xiao Wang; Hendrik Borras; Bernhard Klein; Holger Fröning (CoRR, 2025)

Probabilistic photonic computing for AI. - Frank Brückerhoff-Plückelmann; Anna P. Ovvyan; Akhil Varri; Hendrik Borras; Bernhard Klein; Lennart Meyer; C. David Wright; Harish Bhaskaran; Syed Ghazi Sarwat; Abu Sebastian; Holger Fröning; Wolfram H. P. Pernice (Nat. Comput. Sci., 2025)