1. Athanassopoulos, S., Mavrommatis, E., Gernoth, K. A., Clark, J. W. (1998): To be published.
2. Clark, J. W., Gazula, S., Gernoth, K. A., Hasenbein, J., Prater, J. S., Bohr, H. (1992): Collective Computation of Many-Body Properties by Neural Networks. Recent Progress in Many-Body Theories, Vol. 3, edited by Ainsworth, T. L., Campbell, C. E., Clements, B. E., Krotscheck, E. (Plenum Press, New York), 371–386.
3. Clark, J. W., Gernoth, K. A. (1992): Teaching Neural Networks to do Science. Structure: From Physics to General Systems, Vol. 2, edited by Marinaro, M., Scarpetta, G. (World Scientific, Singapore), 64–77.
4. Clark, J. W., Gernoth, K. A. (1995): Statistical Modeling of Nuclear Masses Using Neural Network Algorithms. Condensed Matter Theories, Vol. 10, edited by Casas, M., de Llano, M., Navarro, J., Polls, A. (Nova Science Publishers, Commack, NY), 317–333.
5. Clark, J. W., Gernoth, K. A., Dittmar, S., Ristig, M. L. (1999): Higher-Order Probabilistic Perceptrons as Bayesian Inference Engines. To be published.