More information Zitong Ye et al, Universal and High-Fidelity Resolution Extending for Fluorescence Microscopy Using a Single-Training Physics-Informed Sparse Neural Network, Intelligent Computing ...

Physics-Informed Neural Networks (PINNs) augment traditional neural architectures by embedding the governing equations of physical systems directly into the loss function. Instead of solely minimising ...

Short video shows the neural network training results and reproduction of flocking from real-world data. Credit: Cell Reports Physical Science Learning local rules with physics-informed AI To address ...