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A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Optimizing Dynamic Aperture Studies with Active Learning

Deep Learning Generalization with Limited and Noisy Labels

Leveraging Unlabeled Data to Track Memorization

Supervised learning and inference of spiking neural networks with temporal coding

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Neural ADMIXTURE for rapid genomic clustering

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems