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 ...

There are few scientific methods more elegantly simple than "just sprinkle it on top." Researchers at Tohoku University and ...

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 ...