Chaotic systems have many interesting features such as sensitivity on initial condition and system parameter, ergodicity and mixing properties. In this paper, we exploit these int...
We present a novel approach to constraintbased causal discovery, that takes the form of straightforward logical inference, applied to a list of simple, logical statements about ca...
Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
This paper addresses modeling and inference for localized calcium release events observed in cardiac muscle tissue known as sparks, a recently discovered and little-understood phe...
Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the p...