Chapter

Bayesian neural networks and dimensionality reduction
In conducting non-linear dimensionality reduction and feature learning, it is common to suppose that the data lie near a …
Deborshee Sen, Theodore Papamarkou, David Dunson
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Mapping the state of the art: artificial intelligence for decision making in financial crime
This chapter provides an overview of the recent literature on the diverse applications of artificial intelligence-based solutions to …
Borja Martínez, Richard Allmendinger, Hadi Akbarzadeh Khorshidi, Theodore Papamarkou, Andre Feitas, Johanne Trippas, Markos Zachariadis, Nicholas Lord, Katie Benson
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Monte Carlo methods and zero variance principle
The principle dates back to 1999, when it was introduced in the physics literature by [3]. The physical nomenclature would broadly …
Theodore Papamarkou, Antonietta Mira, Mark Girolami
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The silicon trypanosome: a test case of iterative model extension in systems biology
The African trypanosome, Trypanosoma brucei, is a unicellular parasite causing African Trypanosomiasis (sleeping sickness in humans and …
Fiona Achcar, Abeer Fadda, Jurgen R. Haanstra, Eduard J. Kerkhoven, Dong-Hyun Kim, Alejandro E. Leroux, Theodore Papamarkou, Federico Rojas, Barbara M. Bakker, Michael P. Barrett, Christine Clayton, Mark Girolami, R. Luise Krauth-Siegel, Keith R. Matthews, Rainer Breitling
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Two aspects of optimum CSK communication: spreading and decoding
This paper focuses on the optimization of performance of single-user chaos shift-keying (CSK). More efficient signal transmission is …
Theodore Papamarkou
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