6 papers
Leveraging dendritic properties to advance machine learning and neuro-inspired computing
Michalis Pagkalos, Roman Makarov, Panayiota Poirazi
The brain is a remarkably capable and efficient system. It can process and store huge amounts of noisy and unstructured information using minimal energy. In contrast, current artif…
Dendrites and Efficiency: Optimizing Performance and Resource Utilization
Roman Makarov, Michalis Pagkalos, Panayiota Poirazi
The brain is a highly efficient system evolved to achieve high performance with limited resources. We propose that dendrites make information processing and storage in the brain mo…
Pricing Step Options under the CEV and other Solvable Diffusion Models
Giuseppe Campolieti, Roman N. Makarov, Karl Wouterloot
We consider a special family of occupation-time derivatives, namely proportional step options introduced by Linetsky in [Math. Finance, 9, 55--96 (1999)]. We develop new closed-for…
Bridge Copula Model for Option Pricing
Giuseppe Campolieti, Roman N. Makarov, Andrey Vasiliev
In this paper we present a new multi-asset pricing model, which is built upon newly developed families of solvable multi-parameter single-asset diffusions with a nonlinear smile-sh…
Exact Simulation of Bessel Diffusions
Roman N. Makarov, Devin Glew
We consider the exact path sampling of the squared Bessel process and some other continuous-time Markov processes, such as the CIR model, constant elasticity of variance diffusion…
Dual Stochastic Transformations of Solvable Diffusions
Giuseppe Campolieti, Roman N. Makarov
We present new extensions to a method for constructing several families of solvable one-dimensional time-homogeneous diffusions whose transition densities are obtainable in analyti…