GeoTorch enables constrained optimization on neural network parameters by providing parametrizations for common constraints like orthogonality, low-rank matrices, symmetric and skew-symmetric matrices, and sphere constraints. It integrates with standard PyTorch optimizers without requiring changes to training code. The library targets researchers and practitioners needing structured parameter spaces in deep learning models.