Introduction Ordinary linear differential equations can be solved as trajectories given some initial conditions. But what if your initial conditions are given as distributions of probability? It turns out that the problem is relatively simple to solve. Transformation of Random Variables If we have a random system described as $latex dot{X}(t) = f(X(t),t) qquad X(t_0) … Continue reading Solving Ordinary Linear Differential Equations with Random Initial Conditions

# Tag: joint distribution

# Introduction to Regression Using Gaussian Processes

Introduction When trying to describe data using a function you often know something about the process generating the data a priori. When you do not completely understand why the data looks like it does but want to try to describe it any way you can start trying different things ad hoc. A couple of years … Continue reading Introduction to Regression Using Gaussian Processes