Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. - Simon Wiedemann; Temesgen Mehari; Kevin Kepp; Wojciech Samek (CVPR Workshops, 2020)

Multi-Class ECG Feature Importance Rankings: Cardiologists vs Algorithms. - Philip J. Aston; Temesgen Mehari; Alen Bosnjakovic; Peter M. Harris; Ashish Sundar; Steven E. Williams; Olaf Dössel; Axel Loewe; Claudia Nagel; Nils Strodthoff (CinC, 2022)

Self-supervised representation learning from 12-lead ECG data. - Temesgen Mehari; Nils Strodthoff (Comput. Biol. Medicine, 2022)

Advancing the State-of-the-Art for ECG Analysis through Structured State Space Models. - Temesgen Mehari; Nils Strodthoff (CoRR, 2022)

Towards Quantitative Precision for ECG Analysis: Leveraging State Space Models, Self-Supervision and Patient Metadata. - Temesgen Mehari; Nils Strodthoff (IEEE J. Biomed. Health Informatics, 2023)

Explaining deep learning for ECG analysis: Building blocks for auditing and knowledge discovery. - Patrick Wagner 002; Temesgen Mehari; Wilhelm Haverkamp; Nils Strodthoff (Comput. Biol. Medicine, 2024)

ECG Feature Importance Rankings: Cardiologists Vs. Algorithms. - Temesgen Mehari; Ashish Sundar; Alen Bosnjakovic; Peter M. Harris; Steven E. Williams; Axel Loewe; Olaf Dössel; Claudia Nagel; Nils Strodthoff; Philip J. Aston (IEEE J. Biomed. Health Informatics, 2024)