Production Scheduling in Complex Job Shops from an Industry 4.0 Perspective: A Review and Challenges in the Semiconductor Industry. - Bernd Waschneck; Thomas Altenmüller; Thomas Bauernhansl; Andreas Kyek (SAMI@iKNOW, 2016)

Case Study on Operator Compliance to Scheduling Decisions in Semiconductor Manufacturing. - Bernd Waschneck; Thomas Altenmüller; Thomas Bauernhansl; Andreas Kyek (CASE, 2018)

Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions. - Simon Mittermaier; Ludwig Kürzinger; Bernd Waschneck; Gerhard Rigoll (ICASSP, 2020)

Autonome Entscheidungsfindung in der Produktionssteuerung komplexer Werkstattfertigungen. - Bernd Waschneck (Fraunhofer Verlag, 2020)

Squeeze-and-Threshold Based Quantization for Low-Precision Neural Networks. - Binyi Wu; Bernd Waschneck; Christian Mayr 001 (EANN, 2021)

dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference. - Elias Trommer; Bernd Waschneck; Akash Kumar 001 (ICCAD, 2021)

Compiler Toolchains for Deep Learning Workloads on Embedded Platforms. - Max Sponner; Bernd Waschneck; Akash Kumar 001 (CoRR, 2021)

Industry-track: Towards Agile Design of Neural Processing Unit. - Binyi Wu; Wolfgang Furtner; Bernd Waschneck; Christian Mayr 001 (CODES+ISSS, 2022)

Neural Architecture Search for Low-Precision Neural Networks. - Binyi Wu; Bernd Waschneck; Christian Mayr 001 (ICANN (4), 2022)

Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks. - Elias Trommer; Bernd Waschneck; Akash Kumar 001 (ICCAD, 2022)

Prototyping of Low-Cost Configurable Sparse Neural Processing Unit with Buffer and Mixed-Precision Reshapeable MAC Array. - Binyi Wu; Wolfgang Furtner; Bernd Waschneck; Christian Mayr 001 (ICPADS, 2022)

Hardware-Efficient Ultrasonic Entrance Counting: Comparing Different Machine Learning Approaches. - Tim Langer; Bernd Waschneck; Johannes Partzsch; Florian Kelber; Christian Mayr 001 (ICPR, 2022)

Convolutional Neural Networks Quantization with Attention. - Binyi Wu; Bernd Waschneck; Christian Georg Mayr (CoRR, 2022)

Convolutional Neural Networks Quantization with Double-Stage Squeeze-and-Threshold. - Binyi Wu; Bernd Waschneck; Christian Georg Mayr (Int. J. Neural Syst., 2022)

High-Throughput Approximate Multiplication Models in PyTorch. - Elias Trommer; Bernd Waschneck; Akash Kumar 001 (DDECS, 2023)

Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing. - Max Sponner; Julius Ott; Lorenzo Servadei; Bernd Waschneck; Robert Wille; Akash Kumar 001 (CoRR, 2023)

Harnessing Temporal Information for Efficient Edge AI. - Max Sponner; Lorenzo Servadei; Bernd Waschneck; Robert Wille; Akash Kumar 001 (FMEC, 2024)

Efficient Post-training Augmentation for Adaptive Inference in Heterogeneous and Distributed IoT Environments. - Max Sponner; Lorenzo Servadei; Bernd Waschneck; Robert Wille; Akash Kumar 001 (SAMOS, 2024)

Leveraging Temporal Patterns: Automated Augmentation to Create Temporal Early Exit Networks for Efficient Edge AI. - Max Sponner; Lorenzo Servadei; Bernd Waschneck; Robert Wille; Akash Kumar 001 (IEEE Access, 2024)

Temporal Decisions: Leveraging Temporal Correlation for Efficient Decisions in Early Exit Neural Networks. - Max Sponner; Lorenzo Servadei; Bernd Waschneck; Robert Wille; Akash Kumar 001 (CoRR, 2024)

QoS-Nets: Adaptive Approximate Neural Network Inference. - Elias Trommer; Bernd Waschneck; Akash Kumar 001 (CoRR, 2024)

Automating application-driven customization of ASIPs: A survey. - Eslam Hussein; Bernd Waschneck; Christian Mayr 001 (J. Syst. Archit., 2024)

Adapting Neural Networks at Runtime: Current Trends in At-Runtime Optimizations for Deep Learning. - Max Sponner; Bernd Waschneck; Akash Kumar 001 (ACM Comput. Surv., 2024)

Smaller Together: Groupwise Encoding of Sparse Neural Networks. - Elias Trommer; Bernd Waschneck; Akash Kumar 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Fast Retraining of Approximate CNNs for High Accuracy. - Elias Trommer; Bernd Waschneck; Akash Kumar 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)