Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). - Arturo Marbán; Daniel Becking; Simon Wiedemann; Wojciech Samek (CVPR Workshops, 2020)

ECQ x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs. - Daniel Becking; Maximilian Dreyer; Wojciech Samek; Karsten Müller 001; Sebastian Lapuschkin (xxAI@ICML, 2020)

Encoder Optimizations For The NNR Standard On Neural Network Compression. - Paul Haase; Daniel Becking; Heiner Kirchhoffer; Karsten Müller 001; Heiko Schwarz; Wojciech Samek; Detlev Marpe; Thomas Wiegand 001 (ICIP, 2021)

FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4Bit-Compact Multilayer Perceptrons. - Simon Wiedemann; Suhas Shivapakash; Daniel Becking; Pablo Wiedemann; Wojciech Samek; Friedel Gerfers; Thomas Wiegand 001 (IEEE Open J. Circuits Syst., 2021)

Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning. - Daniel Becking; Heiner Kirchhoffer; Gerhard Tech; Paul Haase; Karsten Müller 001; Heiko Schwarz; Wojciech Samek (CVPR Workshops, 2022)

History Dependent Significance Coding for Incremental Neural Network Compression. - Gerhard Tech; Paul Haase; Daniel Becking; Heiner Kirchhoffer; Karsten Müller 001; Jonathan Pfaff; Heiko Schwarz; Wojciech Samek; Detlev Marpe; Thomas Wiegand 001 (ICIP, 2022)

Neural Network Coding of Difference Updates for Efficient Distributed Learning Communication. - Daniel Becking; Karsten Müller 001; Paul Haase; Heiner Kirchhoffer; Gerhard Tech; Wojciech Samek; Heiko Schwarz; Detlev Marpe; Thomas Wiegand 001 (IEEE Trans. Multim., 2024)

Efficient Federated Learning Tiny Language Models for Mobile Network Feature Prediction. - Daniel Becking; Ingo Friese; Karsten Müller 001; Thomas Buchholz; Mandy Galkow-Schneider; Wojciech Samek; Detlev Marpe (CoRR, 2025)