Abstract: Deep learning is increasingly adopted in future communication systems to meet requirements within constrained resources. End-to-end (E2E) autoencoder models leverage deep neural networks for ...

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ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...

A Christian worship leader will hold a concert in Seattle this weekend, even as LGBTQ activists urge city leaders to revoke his permit. Sean Feucht, a Christian singer and conservative activist, is ...

According to Stanford AI Lab, researchers have successfully optimized the classic K-SVD algorithm to achieve performance on par with sparse autoencoders for interpreting transformer-based language ...

According to Chris Olah, the central issue in the ongoing Sparse Autoencoder (SAE) debate is mechanistic faithfulness, which refers to how accurately an interpretability method reflects the internal ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...