Efficient Cholesky decomposition of low-rank updates
We give a short and practical guide to efficiently computing the Cholesky decomposition of matrices perturbed by low-rank updates.
We give a short and practical guide to efficiently computing the Cholesky decomposition of matrices perturbed by low-rank updates.
We give a short illustrated reference guide to the Knowledge Gradient acquisition function with an implementation from scratch in TensorFlow Probability.
We illustrate how to build complicated probability distributions in a modular fashion using the Bijector API from TensorFlow Probability.