Simon Wiedemann

29 papers B 4Journal 20Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	From Classical Data to Quantum Advantage - Quantum Policy Evaluation on Quantum Hardware. CoRR Daniel Hein, Simon Wiedemann, Markus Baumann, Patrik Felbinger, Justin Klein, Maximilian Schieder, Jonas Stein, Daniëlle Schuman, Thomas Cope, Steffen Udluft
2023	J	`jnl`	A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography. CoRR Simon Wiedemann, Reinhard Heckel
2023	J	`jnl`	Quantum Policy Iteration via Amplitude Estimation and Grover Search - Towards Quantum Advantage for Reinforcement Learning. Trans. Mach. Learn. Res. Simon Wiedemann, Daniel Hein, Steffen Udluft, Christian B. Mendl
2022	—	`—`	Compact and efficient representations of deep neural networks. Simon Wiedemann
2022	J	`jnl`	Quantum Policy Iteration via Amplitude Estimation and Grover Search - Towards Quantum Advantage for Reinforcement Learning. CoRR Simon Wiedemann, Daniel Hein, Steffen Udluft, Christian B. Mendl
2021	J	`jnl`	FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4Bit-Compact Multilayer Perceptrons. IEEE Open J. Circuits Syst. Simon Wiedemann, Suhas Shivapakash, Daniel Becking, Pablo Wiedemann, Wojciech Samek, Friedel Gerfers, Thomas Wiegand
2021	J	`jnl`	Pruning by explaining: A novel criterion for deep neural network pruning. Pattern Recognit. Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Alexander Binder, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2020	J	`jnl`	Compact and Computationally Efficient Representation of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2020	J	`jnl`	DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. IEEE J. Sel. Top. Signal Process. Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Tung Nguyen, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek
2020	B	`conf`	Deepcabac: Plug & Play Compression of Neural Network Weights and Weight Updates. ICIP David Neumann, Felix Sattler, Heiner Kirchhoffer, Simon Wiedemann, Karsten Müller, Heiko Schwarz, Thomas Wiegand, Detlev Marpe, Wojciech Samek
2020	B	`conf`	Dependent Scalar Quantization For Neural Network Compression. ICIP Paul Haase, Heiko Schwarz, Heiner Kirchhoffer, Simon Wiedemann, Talmaj Marinc, Arturo Marbán, Karsten Müller, Wojciech Samek, Detlev Marpe, Thomas Wiegand
2020	—	`conf`	Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. CVPR Workshops Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek
2020	J	`jnl`	Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training. CoRR Simon Wiedemann, Temesgen Mehari, Kevin Kepp, Wojciech Samek
2020	J	`jnl`	FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons. CoRR Simon Wiedemann, Suhas Shivapakash, Pablo Wiedemann, Daniel Becking, Wojciech Samek, Friedel Gerfers, Thomas Wiegand
2020	—	`conf`	Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). CVPR Workshops Arturo Marbán, Daniel Becking, Simon Wiedemann, Wojciech Samek
2020	J	`jnl`	Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T). CoRR Arturo Marbán, Daniel Becking, Simon Wiedemann, Wojciech Samek
2020	J	`jnl`	Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data. IEEE Trans. Neural Networks Learn. Syst. Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2019	J	`jnl`	DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks. CoRR Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Tung Nguyen, Ahmed Osman, Detlev Marpe, Heiko Schwarz, Thomas Wiegand, Wojciech Samek
2019	J	`jnl`	DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression. CoRR Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marbán, Talmaj Marinc, David Neumann, Ahmed Osman, Detlev Marpe, Heiko Schwarz, Thomas Wiegand, Wojciech Samek
2019	B	`conf`	Entropy-Constrained Training of Deep Neural Networks. IJCNN Simon Wiedemann, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek
2019	J	`jnl`	Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning. CoRR Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2019	J	`jnl`	Robust and Communication-Efficient Federated Learning from Non-IID Data. CoRR Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2019	B	`conf`	Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. IJCNN Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2018	J	`jnl`	Compact and Computationally Efficient Representation of Deep Neural Networks. CoRR Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2018	J	`jnl`	Entropy-Constrained Training of Deep Neural Networks. CoRR Simon Wiedemann, Arturo Marbán, Klaus-Robert Müller, Wojciech Samek
2018	J	`jnl`	Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. CoRR Felix Sattler, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
2017	J	`jnl`	A discrete-time queueing network approach to performance evaluation of autonomous vehicle storage and retrieval systems. Int. J. Prod. Res. Martin Epp, Simon Wiedemann, Kai Furmans
2017	—	`conf`	Comparison between linear- and nonlinear-feedback control for a synchronous reluctance machine. ISIE Anton H. Tamas, Claudia S. Martis, Simon Wiedemann, Ralph M. Kennel
2017	—	`conf`	Encoderless self-commissioning and identification of synchronous reluctance machines at standstill. ISIE Simon Wiedemann, Ralph M. Kennel