Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

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 ...

Got a modern Nvidia or AMD graphics card? Custom Llamas are only a few commands and a little data prep away Hands on Large language models (LLMs) are remarkably effective at generating text and ...

Python implementation of Markov Networks for neural computing - updated for modern NumPy. - jtatman/MarkovNetworkNew ...

MotorNet is a Python toolbox for training artificial neural networks to control arbitrarily complex, differentiable, and biomechanically realistic musculo-skeletal effectors on user-defined ...

In our designed multi-input deep convolutional neural network, each channel inputs one modal of physiological signal; therefore, by adding input channels, the model can take multi-modal physiological ...