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Fraunhofer Institute for Integrated Circuits IIS, University of Technology N眉rnberg (UTN)
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CPDA aligns class-conditional latent paths, outperforming 30 existing methods in unsupervised time-series domain adaptation.
Energy-aware DNN design can now be optimized offline, paving the way for truly autonomous AI on intermittent power sources.
Quick retraining of reinforcement learning policies to adapt to changing safety constraints is now possible without retraining the entire network.
