By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia

A Bayesian functional regression framework built on RKHS's and reversible jump MCMC.

Empirical analysis of the Laplace and neural tangent kernel reproducing kernel Hilbert space (RKHS)

1-D Normal Splines in Julia

Code for the paper "Convergent Methods for Koopman Operators on Reproducing Kernel Hilbert Spaces".

Finite-Sample Integral Gaussian Processes

A functional regression framework built on Bayesian inference and RKHS's.

My PhD thesis: Regression modelling using priors depending on Fisher information covariance kernels (I-priors)

Binary and multinomial probit regression using I-priors

An R package for I-prior regression

Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.

Multimodal LLM hallucination quantification via KL-smoothed scores + spectral/energy models (RKHS, hypergraphs).

Multivariate Normal Hermite-Birkhoff Uniform Smoothing Splines in Julia

Lifting-based Uncertain Control Invariant Dynamics

A generalized reinforcement learning framework for structured action representations and adaptive decision-making in evolving systems.

Structure-Preserving Nonlinear Sufficient Dimension Reduction

Additive interaction modelling using I-priors

Reproducing Kernel Hilbert Space: kernels, MMD, and Dense Associative Memory (LSE/LSR energy)

This repository provides code for the simulations and experiments in our paper: Metric Learning in an RKHS @ The 41st Conference on Uncertainty in Artificial Intelligence (UAI 2025).