However, the comprehensive interpretation of neural networks remains inadequately explored. To address this challenge and develop a fully interpretable network, we propose a transparent operator ...

Existing three-dimensional (3D) neuronal culture technology has limitations in brain research due to the difficulty of ...

A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional ...

Next, unlike conventional physics-informed neural networks that only utilize macroscopic physical information, we constrain the training of the neural network by using dynamic metabolic flux analysis ...

FramePack is a next-frame (next-frame-section) prediction neural network structure that generates videos progressively. FramePack compresses input contexts to a constant length so that the generation ...

Using two phase-change memory devices per synapse, a three-layer perceptron network with 164 885 synapses is trained on a subset (5000 examples) of the MNIST database of handwritten digits using a ...

Such abnormal neural activities are thought to arise from a failure in the self-organizing mechanisms that sustain criticality. For example, numerical simulations of spiking neural networks have ...