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cs.MS2026
Tensor Network Kernel Machines: A JAX Framework for Machine Learning and Nonlinear System Identification
Albert Saiapin, Kim Batselier
Developing nonlinear models that are both expressive and computationally efficient remains a challenge in machine learning and nonlinear system identification. Tensor network kerne…
stat.ML2026
Laplace Approximation for Bayesian Tensor Network Kernel Machines
Albert Saiapin, Kim Batselier
Uncertainty estimation is essential for robust decision-making in the presence of ambiguous or out-of-distribution inputs. Gaussian Processes (GPs) are classical kernel-based model…