Neural Circuit Policies (NCPs) are sparse recurrent neural networks designed for auditable autonomy and efficient time-series processing. The library provides reference implementations of NCP, LTC, and CfC architectures in both PyTorch and TensorFlow/Keras, including utilities for working with irregularly sampled time-series data. Published work includes papers in Nature Machine Intelligence on closed-form continuous-time neural networks.