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3Advancing blood glucose prediction with neural architecture search and deep reinforcement learning for type 1 diabetics
P. Domanski, A. Ray, K. Lafata, F. Firouzi, K. Chakrabarty, and D. Pflüger. Biocybernetics and Biomedical Engineering, 44 (3): 481--500 (2024)
a year ago by @domanspr
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3Blood Glucose Prediction for Type-1 Diabetics using Deep Reinforcement Learning
P. Domanski, A. Ray, F. Firouzi, K. Lafata, K. Chakrabarty, and D. Pflüger. 2023 IEEE International Conference on Digital Health (ICDH), page 339-347. (July 2023)
2 years ago by @domanspr
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7Training Large Language Models for System-Level Test Program Generation Targeting Non-functional Properties
D. Schwachhofer, P. Domanski, S. Becker, S. Wagner, M. Sauer, D. Pflüger, and I. Polian. 2024 IEEE European Test Symposium (ETS), page 1-4. (May 2024)
a year ago by @domanspr
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5ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems
P. Domanski, D. Pflüger, R. Latty, and J. Rivoir. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), page 1357-1364. Piscataway, IEEE, (December 2021)
2 years ago by @domanspr
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2Intelligent Methods for Test and Reliability
H. Amrouch, J. Anders, S. Becker, M. Betka, G. Bleher, P. Domanski, N. Elhamawy, T. Ertl, A. Gatzastras, P. Genssler and 25 other author(s). 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), page 969-974. (March 2022)
2 years ago by @domanspr
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4ML-TIME: ML-driven Timing Analysis of Integrated Circuits in the Presence of Process Variations and Aging Effects
X. Tan, P. Domanski, S. Banerjee, and K. Chakrabarty. Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, page 1–9. New York, NY, USA, Association for Computing Machinery, (Sep 9, 2024)
12 months ago by @domanspr
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3Learn to Tune: Robust Performance Tuning in Post-Silicon Validation
P. Domanski, D. Pflüger, and R. Latty. 2023 IEEE European Test Symposium (ETS), page 1-4. (May 2023)
2 years ago by @domanspr
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4High-Fidelity Simulation of a Cartpole for Sim-to-Real Deep Reinforcement Learning
L. Bantel, P. Domanski, and D. Pflüger. 2024 4th Interdisciplinary Conference on Electrics and Computer (INTCEC), page 1-6. (June 2024)
a year ago by @domanspr
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4Self-Learning Tuning for Post-Silicon Validation
P. Domanski, D. Pflüger, J. Rivoir, and R. Latty. (2022)Testmethoden und Zuverlässigkeit von Schaltungen und Systemen, TuZ 2022..
2 years ago by @domanspr
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4Large Language Models to Generate System-Level Test Programs Targeting Non-functional Properties
D. Schwachhofer, P. Domanski, S. Becker, S. Wagner, M. Sauer, D. Pflüger, and I. Polian. (2024)Testmethoden und Zuverlässigkeit von Schaltungen und Systemen, TuZ 2024..
a year ago by @domanspr
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PUMA

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3Advancing blood glucose prediction with neural architecture search and deep reinforcement learning for type 1 diabetics

3Blood Glucose Prediction for Type-1 Diabetics using Deep Reinforcement Learning

7Training Large Language Models for System-Level Test Program Generation Targeting Non-functional Properties

5ORSA: Outlier Robust Stacked Aggregation for Best- and Worst-Case Approximations of Ensemble Systems

2Intelligent Methods for Test and Reliability

4ML-TIME: ML-driven Timing Analysis of Integrated Circuits in the Presence of Process Variations and Aging Effects

3Learn to Tune: Robust Performance Tuning in Post-Silicon Validation

4High-Fidelity Simulation of a Cartpole for Sim-to-Real Deep Reinforcement Learning

4Self-Learning Tuning for Post-Silicon Validation

4Large Language Models to Generate System-Level Test Programs Targeting Non-functional Properties

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