Segui
Dr. Bernd Waschneck
Titolo
Citata da
Citata da
Anno
Optimization of global production scheduling with deep reinforcement learning
B Waschneck, A Reichstaller, L Belzner, T Altenmüller, T Bauernhansl, ...
Procedia Cirp 72, 1264-1269, 2018
4052018
Deep reinforcement learning for semiconductor production scheduling
B Waschneck, A Reichstaller, L Belzner, T Altenmüller, T Bauernhansl, ...
2018 29th annual SEMI advanced semiconductor manufacturing conference (ASMC …, 2018
1662018
Production Scheduling in Complex Job Shops from an Industry 4.0 Perspective: A Review and Challenges in the Semiconductor Industry.
B Waschneck, T Altenmüller, T Bauernhansl, A Kyek
SAMI@ iKNOW 1793, 109, 2016
1182016
Reinforcement learning for an intelligent and autonomous production control of complex job-shops under time constraints
T Altenmüller, T Stüker, B Waschneck, A Kuhnle, G Lanza
Production Engineering, 1-10, 2020
842020
Small-footprint keyword spotting on raw audio data with sinc-convolutions
S Mittermaier, L Kürzinger, B Waschneck, G Rigoll
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
762020
Opportunistic maintenance scheduling with deep reinforcement learning
Alexander Valet, Thomas Altenmüller, Bernd Waschneck, Marvin Carl May ...
Journal of Manufacturing Systems 64, 518-534, 2022
522022
Autonome Entscheidungsfindung in der Produktionssteuerung komplexer Werkstattfertigungen
B Waschneck
Stuttgart: Fraunhofer Verlag, 2020
132020
dCSR: A memory-efficient sparse matrix representation for parallel neural network inference
E Trommer, B Waschneck, A Kumar
2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2021
92021
Adapting neural networks at runtime: Current trends in at-runtime optimizations for deep learning
M Sponner, B Waschneck, A Kumar
ACM Computing Surveys 56 (10), 1-40, 2024
82024
Combining gradients and probabilities for heterogeneous approximation of neural networks
E Trommer, B Waschneck, A Kumar
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided …, 2022
72022
AI-driven performance modeling for AI inference workloads
M Sponner, B Waschneck, A Kumar
Electronics 11 (15), 2316, 2022
72022
Compiler toolchains for deep learning workloads on embedded platforms
M Sponner, B Waschneck, A Kumar
arXiv preprint arXiv:2104.04576, 2021
72021
Temporal patience: Efficient adaptive deep learning for embedded radar data processing
M Sponner, J Ott, L Servadei, B Waschneck, R Wille, A Kumar
arXiv preprint arXiv:2309.05686, 2023
62023
Convolutional neural networks quantization with double-stage squeeze-and-threshold
B Wu, B Waschneck, CG Mayr
International Journal of Neural Systems 32 (12), 2250051, 2022
62022
Squeeze-and-threshold based quantization for low-precision neural networks
B Wu, B Waschneck, C Mayr
International Conference on Engineering Applications of Neural Networks, 232-243, 2021
52021
Unified frontend and backend industrie 4.0 roadmap for semiconductor manufacturing
B Waschneck, LWF Brian, KCW Benny, C Rippler, G Schmid
Proceedings of the 2017 International Conference on Knowledge Technologies …, 2017
52017
Toward combined transport and optical studies of the 0.7‐anomaly in a quantum point contact
E Schubert, J Heyder, F Bauer, B Waschneck, W Stumpf, W Wegscheider, ...
physica status solidi (b) 251 (9), 1931-1937, 2014
42014
High-throughput approximate multiplication models in PyTorch
E Trommer, B Waschneck, A Kumar
2023 26th International Symposium on Design and Diagnostics of Electronic …, 2023
32023
Case Study on Operator Compliance to Scheduling Decisions in Semiconductor Manufacturing
B Waschneck, T Altenmüller, T Bauernhansl, A Kyek
14th IEEE International Conference on Automation Science and Engineering (CASE), 2018
32018
Harnessing Temporal Information for Efficient Edge AI
M Sponner, L Servadei, B Waschneck, R Wille, A Kumar
2024 9th International Conference on Fog and Mobile Edge Computing (FMEC), 5-13, 2024
22024
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–20