Comparison between linear- and nonlinear-feedback control for a synchronous reluctance machine. - Anton H. Tamas; Claudia S. Martis; Simon Wiedemann; Ralph M. Kennel (ISIE, 2017)

Encoderless self-commissioning and identification of synchronous reluctance machines at standstill. - Simon Wiedemann; Ralph M. Kennel (ISIE, 2017)

A discrete-time queueing network approach to performance evaluation of autonomous vehicle storage and retrieval systems. - Martin Epp; Simon Wiedemann; Kai Furmans (Int. J. Prod. Res., 2017)

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. - Felix Sattler; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (IJCNN, 2019)

Entropy-Constrained Training of Deep Neural Networks. - Simon Wiedemann; Arturo Marbán; Klaus-Robert Müller; Wojciech Samek (IJCNN, 2019)

Robust and Communication-Efficient Federated Learning from Non-IID Data. - Felix Sattler; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (CoRR, 2019)

DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression. - Simon Wiedemann; Heiner Kirchhoffer; Stefan Matlage; Paul Haase; Arturo Marbán; Talmaj Marinc; David Neumann; Ahmed Osman; Detlev Marpe; Heiko Schwarz; Thomas Wiegand 001; Wojciech Samek (CoRR, 2019)

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. - Simon Wiedemann; Heiner Kirchhoffer; Stefan Matlage; Paul Haase; Arturo Marbán; Talmaj Marinc; David Neumann; Tung Nguyen 001; Ahmed Osman; Detlev Marpe; Heiko Schwarz; Thomas Wiegand 001; et al. (CoRR, 2019)

Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning. - Seul-Ki Yeom; Philipp Seegerer; Sebastian Lapuschkin; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (CoRR, 2019)

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

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)

Dependent Scalar Quantization For Neural Network Compression. - Paul Haase; Heiko Schwarz; Heiner Kirchhoffer; Simon Wiedemann; Talmaj Marinc; Arturo Marbán; Karsten Müller 001; Wojciech Samek; Detlev Marpe; Thomas Wiegand 001 (ICIP, 2020)

Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates. - David Neumann; Felix Sattler; Heiner Kirchhoffer; Simon Wiedemann; Karsten Müller 001; Heiko Schwarz; Thomas Wiegand 001; Detlev Marpe; Wojciech Samek (ICIP, 2020)

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. - Simon Wiedemann; Heiner Kirchhoffer; Stefan Matlage; Paul Haase; Arturo Marbán; Talmaj Marinc; David Neumann; Tung Nguyen 001; Heiko Schwarz; Thomas Wiegand 001; Detlev Marpe; Wojciech Samek (IEEE J. Sel. Top. Signal Process., 2020)

Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. - Felix Sattler; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (IEEE Trans. Neural Networks Learn. Syst., 2020)

Compact and Computationally Efficient Representation of Deep Neural Networks. - Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (IEEE Trans. Neural Networks Learn. Syst., 2020)

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)

Pruning by explaining: A novel criterion for deep neural network pruning. - Seul-Ki Yeom; Philipp Seegerer; Sebastian Lapuschkin; Alexander Binder; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (Pattern Recognit., 2021)

Compact and efficient representations of deep neural networks. - Simon Wiedemann (2022)

A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography. - Simon Wiedemann; Reinhard Heckel (CoRR, 2023)

Quantum Policy Iteration via Amplitude Estimation and Grover Search - Towards Quantum Advantage for Reinforcement Learning. - Simon Wiedemann; Daniel Hein 001; Steffen Udluft; Christian B. Mendl (Trans. Mach. Learn. Res., 2023)