Researchers at Columbia University Propose the Unbounded Depth Neural Network (UDN): An Infinitely Deep Probabilistic Model that Enables Self-Adaption to the Training Data Without an Upper Limit

While today’s deep neural networks (DNNs) drive AI’s deep-learning revolution, determining a DNN’s appropriate complexity remains challenging. If a DNN is too shallow, its predictive performance will suffer; if it is too deep, it will tend to overfit, and its complexity will result in prohibitively high compute costs. Researchers propose the new unbounded depth neural […]

The post Researchers at Columbia University Propose the Unbounded Depth Neural Network (UDN): An Infinitely Deep Probabilistic Model that Enables Self-Adaption to the Training …

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