Carl Edward Rasmussen

I have very broad interests in probabilistic inference in machine learning, covering both unsupervised, supervised and reinforcement learning. I’m particularly interested in design and evaluation of non-parametric methods such as Gaussian processes and Dirichlet processes. Exact inference in these models is often intractable, so one needs to resort to approximation methods, such as variational techniques or Markov chain Monte Carlo.

Research page: here.