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- GSI Helmholtz Centre for Heavy Ion ResearchDE298 papers
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33 papers · 1 filter
Sharing Knowledge in Multi-Task Deep Reinforcement Learning
Carlo D'Eramo, Davide Tateo, Andrea Bonarini +2
We study the benefit of sharing representations among tasks to enable the effective use of deep neural networks in Multi-Task Reinforcement Learning. We leverage the assumption tha…
Towards the Visualization of Aggregated Class Activation Maps to Analyse the Global Contribution of Class Features
Igor Cherepanov, David Sessler, Alex Ulmer +2
Deep learning (DL) models achieve remarkable performance in classification tasks. However, models with high complexity can not be used in many risk-sensitive applications unless a…
Deep learning based Meta-modeling for Multi-objective Technology Optimization of Electrical Machines
Vivek Parekh, Dominik Flore, Sebastian Schöps
Optimization of rotating electrical machines is both time- and computationally expensive. Because of the different parametrization, design optimization is commonly executed separat…
Deep Learning-enabled MCMC for Probabilistic State Estimation in District Heating Grids
Andreas Bott, Tim Janke, Florian Steinke
Flexible district heating grids form an important part of future, low-carbon energy systems. We examine probabilistic state estimation in such grids, i.e., we aim to estimate the p…
Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems
Mehran Salmani, Saeid Ghafouri, Alireza Sanaee +5
The use of machine learning (ML) inference for various applications is growing drastically. ML inference services engage with users directly, requiring fast and accurate responses.…
Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra
Joachim Schaeffer, Paul Gasper, Esteban Garcia-Tamayo +10
Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and th…