tnkm is a JAX-based library for machine learning with tensor-network parameterizations. It combines kernel methods with low-rank tensor decompositions to build scalable models with explicit rank control. tnkm is intended for research in machine learning, system identification, and time-series modeling.

Features

• CP and TT tensor-network kernel machines
• Polynomial, Fourier, B-spline and other feature maps
• Alternating Least Squares (ALS) and gradient-based optimization (Optax)
• Explicit rank control for balancing model complexity and expressiveness
• JAX-native implementation with JIT compilation and hardware acceleration