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The PRAD-Hybrid CNN (Prostate Adenocarcinoma Hybrid Convolutional Neural Network, PRADHC) model, a novel amalgamation of EfficientNet and Residual Blocks, which was developed and validated, improved the diagnostic accuracy inherent to the original EfficientNet by strategically increasing the number of Convolutional Neu...
This work introduces Conditional-Independence-Regularized Distributional Autoencoders, a framework for learning low-dimensional representations of mixed-type data through conditional distribution matching and structural regularization that achieves strong performance on both synthetic and real-world datasets.
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