jaxley

A differentiable PDE solving framework for machine learning

large population models

A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs

Pytorch differentiable molecular dynamics

Efficient GPU-computing simulation for differentiable crystal plasticity finite element method

A differentiable finite element analysis solver for structural optimization based on JAX

Implementation of a Spiking Neural Network in Tensorflow.

EP-PINNs implementation for 1D and 2D forward and inverse solvers for the Aliev-Panfilov cardiac electrophysiology model. Also includes Matlab finite-differences solver for data generation.

Analysis of single particle tracking data for characterisation of anomalous diffusion, using convolutional neural networks. Submitted to the Anomalous Diffusion (AnDi) Challenge

这是发表在《物理评论快报》(PRL 2025) 的论文《局部聚集和受体全局扩散以实现最佳空间梯度感知》的官方代码。代码包含用于优化细胞表面受体位置的模拟和可视化。