A mixture density network (MDN) Layer for Keras using pure Keras 3 operations. This makes it a bit more simple to experiment with neural networks that predict multiple real-valued variables that can ...
Abstract: The identification and classification of broken conductor faults in power distribution systems (PDSs) is challenging because of the nonlinear and complex nature of the unbalanced three-phase ...
Deep neural networks have been increasingly proposed for automated screening and diagnosis of retinal diseases from optical coherence tomography (OCT), but often provide high-confidence predictions on ...
School of Computer Science and Technology, Shandong University of Technology, Zibo, China. In today’s field of computer vision, human posture recognition is a hot topic of research work. Its main task ...
The onset and progression of pathological heart conditions, such as cardiomyopathy or heart failure, affect its mechanical behaviour due to the remodelling of the myocardial tissues to preserve its ...
Purpose: Bayesian calibration is generally superior to standard direct-search algorithms in that it estimates the full joint posterior distribution of the calibrated parameters. However, there are ...
Organoid cultures are proving to be powerful in vitro models that closely mimic the cellular constituents of their native tissue. Organoids are typically expanded and cultured in a 3D environment ...
A differentiable axiomatic feature attribution method called expected gradients. Tensorflow and PyTorch operations to directly regularize expected gradients attributions during training. Examples of ...
Partial differential equations (PDEs) are among the most ubiquitous tools used in modeling problems in nature. However, solving high-dimensional PDEs has been notoriously difficult due to the “curse ...
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