Artificial intelligence (AI), particularly deep learning models, are often considered black boxes because their ...
New Pharmacokinetic (PK) and Pharmacodynamic Data from Sub-Study in Phase III Trial Strengthens Scientific Basis for RenovoRx ...
Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.
Abstract: Data augmentation is an effective way to overcome the overfitting problem of deep learning models. However, most existing studies on data augmentation work on framelike data (e.g., images), ...
Two things are clear from a University of Michigan analysis of nearly 200,000 Twitter posts between 2012 and 2022. One, ...
The discourse around climate change can lead to anxiety, detachment or resignation because it often stretches language in ...
To speed up computation, deep neural networks (DNNs) usually rely on highly optimized tensor operators. Despite the effectiveness, tensor operators are often defined empirically with ad hoc semantics.
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