Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging. - Dirk Ormoneit; Volker Tresp (NIPS, 1995)

Experiments in predicting the German stock index DAX with density estimating neural networks. - Dirk Ormoneit; Ralph Neuneier (CIFEr, 1996)

Averaging, maximum penalized likelihood and Bayesian estimation for improving Gaussian mixture probability density estimates. - Dirk Ormoneit; Volker Tresp (IEEE Trans. Neural Networks, 1998)

Probability estimating neural networks. - Dirk Ormoneit (Shaker, 1998)

Optimal Kernel Shapes for Local Linear Regression. - Dirk Ormoneit; Trevor Hastie (NIPS, 1999)

A regularization approach to continuous learning with an application to financial derivatives pricing. - Dirk Ormoneit (Neural Networks, 1999)

Kernel-Based Reinforcement Learning in Average-Cost Problems: An Application to Optimal Portfolio Choice. - Dirk Ormoneit; Peter W. Glynn (NIPS, 2000)

Learning and Tracking Cyclic Human Motion. - Dirk Ormoneit; Hedvig Sidenbladh; Michael J. Black; Trevor Hastie (NIPS, 2000)

Learning an Agent's Utility Function by Observing Behavior. - Urszula Chajewska; Daphne Koller; Dirk Ormoneit (ICML, 2001)

Probabilistic Abstraction Hierarchies. - Eran Segal; Daphne Koller; Dirk Ormoneit (NIPS, 2001)

Robust Combination of Local Controllers. - Carlos Guestrin; Dirk Ormoneit (UAI, 2001)

Lattice Particle Filters. - Dirk Ormoneit; Christiane Lemieux; David J. Fleet (UAI, 2001)

Kernel-Based Reinforcement Learning. - Dirk Ormoneit; Saunak Sen (Mach. Learn., 2002)

Kernel-based reinforcement learning in average-cost problems. - Dirk Ormoneit; Peter W. Glynn (IEEE Trans. Autom. Control., 2002)

Representing cyclic human motion using functional analysis. - Dirk Ormoneit; Michael J. Black; Trevor Hastie; Hedvig Kjellström (Image Vis. Comput., 2005)