Bi-Directional DFEs for Plastic Optical Fiber Based In-Vehicle Infotainment System at 2-3Gbit/s. - Yixuan Wang; Lukas Mauch; Joachim Speidel (VTC Fall, 2012)

A new approach for supervised power disaggregation by using a deep recurrent LSTM network. - Lukas Mauch; Bin Yang 009 (GlobalSIP, 2015)

A novel DNN-HMM-based approach for extracting single loads from aggregate power signals. - Lukas Mauch; Bin Yang 009 (ICASSP, 2016)

On semantic image segmentation using deep convolutional neural network with shortcuts and easy class extension. - Chunlai Wang; Lukas Mauch; Ze Guo; Bin Yang 009 (IPTA, 2016)

Selecting optimal layer reduction factors for model reduction of deep neural networks. - Lukas Mauch; Bin Yang 009 (ICASSP, 2017)

A novel layerwise pruning method for model reduction of fully connected deep neural networks. - Lukas Mauch; Bin Yang 009 (ICASSP, 2017)

Graphical User Interface for Medical Deep Learning - Application to Magnetic Resonance Imaging. - Sebastian Milde; Annika Liebgott; Ziwei Wu; Wenyi Feng; Jiahuan Yang; Lukas Mauch; Petros Martirosian; Fabian Bamberg; Konstantin Nikolaou; Sergios Gatidis; Fritz Schick; Bin Yang 009; et al. (APSIPA, 2018)

Automated Detection of Solar Cell Defects with Deep Learning. - Alexander Bartler; Lukas Mauch; Bin Yang 009; Michael Reuter; Liviu Stoicescu (EUSIPCO, 2018)

Automatic Motion Artifact Detection for Whole-Body Magnetic Resonance Imaging. - Thomas Kustner; Marvin Jandt; Annika Liebgott; Lukas Mauch; Petros Martirosian; Fabian Bamberg; Konstantin Nikolaou; Sergios Gatidis; Fritz Schick; Bin Yang 009 (ICASSP, 2018)

Binary Segmentation Based Class Extension in Semantic Image Segmentation Using Convolutional Neural Networks. - Chunlai Wang; Jiawei Yu; Lukas Mauch; Bin Yang 009 (ICIP, 2018)

Least-Squares Based Layerwise Pruning Of Convolutional Neural Networks. - Lukas Mauch; Bin Yang (SSP, 2018)

Neural Network Ensembles to Real-time Identification of Plug-level Appliance Measurements. - Karim Said Barsim; Lukas Mauch; Bin Yang 009 (CoRR, 2018)

A Machine-learning framework for automatic reference-free quality assessment in MRI. - Thomas Küstner; Sergios Gatidis; Annika Liebgott; Martin Schwartz; Lukas Mauch; Petros Martirosian; Holger Schmidt; Nina F. Schwenzer; Konstantin Nikolaou; Fabian Bamberg; Bin Yang 009; Fritz Schick (CoRR, 2018)

Deep Neural Network inference with reduced word length. - Lukas Mauch; Bin Yang (CoRR, 2018)

On the contextual aspects of using deep convolutional neural network for semantic image segmentation. - Chunlai Wang; Lukas Mauch; Mehul Manoj Saxena; Bin Yang 009 (J. Electronic Imaging, 2018)

Subset selection for visualization of relevant image fractions for deep learning based semantic image segmentation. - Lukas Mauch; Chunlai Wang; Bin Yang 009 (J. Frankl. Inst., 2018)

Training Variational Autoencoders with Discrete Latent Variables Using Importance Sampling. - Alexander Bartler; Felix Wiewel; Lukas Mauch; Bin Yang 009 (EUSIPCO, 2019)

Differentiable Quantization of Deep Neural Networks. - Stefan Uhlich; Lukas Mauch; Kazuki Yoshiyama; Fabien Cardinaux; Javier Alonso García; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (CoRR, 2019)

Mixed Precision DNNs: All you need is a good parametrization. - Stefan Uhlich; Lukas Mauch; Fabien Cardinaux; Kazuki Yoshiyama; Javier Alonso García; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (ICLR, 2020)

Efficient Sampling for Predictor-Based Neural Architecture Search. - Lukas Mauch; Stephen Tiedemann; Javier Alonso García; Bac Nguyen Cong; Kazuki Yoshiyama; Fabien Cardinaux; Thomas Kemp (CoRR, 2020)

Iteratively Training Look-Up Tables for Network Quantization. - Fabien Cardinaux; Stefan Uhlich; Kazuki Yoshiyama; Javier Alonso García; Lukas Mauch; Stephen Tiedemann; Thomas Kemp; Akira Nakamura (IEEE J. Sel. Top. Signal Process., 2020)

DNN Quantization with Attention. - Ghouthi Boukli Hacene; Lukas Mauch; Stefan Uhlich; Fabien Cardinaux (CoRR, 2021)

A Statistical Model for Predicting Generalization in Few-Shot Classification. - Yassir Bendou; Vincent Gripon; Bastien Pasdeloup; Lukas Mauch; Stefan Uhlich; Fabien Cardinaux; Ghouthi Boukli Hacene; Javier Alonso García (CoRR, 2022)

A Statistical Model for Predicting Generalization in Few-Shot Classification. - Yassir Bendou; Vincent Gripon; Bastien Pasdeloup; Giulia Lioi; Lukas Mauch; Stefan Uhlich; Fabien Cardinaux; Ghouthi Boukli Hacene; Javier Alonso García (EUSIPCO, 2023)

Efficient Training of Deep Equilibrium Models. - Bac Nguyen Cong; Lukas Mauch (CoRR, 2023)

DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation. - Pau Mulet Arabi; Alec Flowers; Lukas Mauch; Fabien Cardinaux (CoRR, 2023)

Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning. - Yassir Bendou; Vincent Gripon; Bastien Pasdeloup; Giulia Lioi; Lukas Mauch; Fabien Cardinaux; Ghouthi Boukli Hacene (CoRR, 2023)

Analyzing Few-Shot Neural Architecture Search in a Metric-Driven Framework. - Timotée Ly-Manson; Mathieu Léonardon; Abdeldjalil Aïssa-El-Bey; Ghouthi Boukli Hacene; Lukas Mauch (AutoML, 2024)

SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning. - Bac Nguyen; Stefan Uhlich; Fabien Cardinaux; Lukas Mauch; Marzieh Edraki; Aaron C. Courville (ECCV (69), 2024)

Order-Preserving GFlowNets. - Yihang Chen; Lukas Mauch (ICLR, 2024)

LLM meets Vision-Language Models for Zero-Shot One-Class Classification. - Yassir Bendou; Giulia Lioi; Bastien Pasdeloup; Lukas Mauch; Ghouthi Boukli Hacene; Fabien Cardinaux; Vincent Gripon (CoRR, 2024)

Schemato - An LLM for Netlist-to-Schematic Conversion. - Ryoga Matsuo; Stefan Uhlich; Arun Venkitaraman; Andrea Bonetti; Chia-Yu Hsieh; Ali Momeni 002; Lukas Mauch; Augusto Capone; Eisaku Ohbuchi; Lorenzo Servadei (CoRR, 2024)

Least-squares based layerwise pruning of Deep Neural Networks. - Lukas Mauch (2024)

A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models. - Reda Bensaid; Vincent Gripon; François Leduc-Primeau; Lukas Mauch; Ghouthi Boukli Hacene; Fabien Cardinaux (Trans. Mach. Learn. Res., 2025)

On multi-token prediction for efficient LLM inference. - Somesh Mehra; Javier Alonso García; Lukas Mauch (CoRR, 2025)

Global-Order GFlowNets. - Lluís Pastor Pérez; Javier Alonso García; Lukas Mauch (CoRR, 2025)