Designing chain reaction contraptions from causal graphs

Learning Causal AMP Chain Graphs

Andersson-Madigan-Perlman chain graphs were originally introduced to represent independence models. They have recently been shown to be suitable for representing causal models with additive noise. In this paper, we present an algorithm for learning causal chain graphs. The algorithm builds on the ideas by Hoyer et al. (2009), i.e. it exploits the nonlinearities in the data to identify the direc...

Evaluating Causal effects using Chain Event Graphs

Generating Possible Conflicts From Bond Graphs Using Temporal Causal Graphs

Accurate modeling mechanisms play an important role in model-based diagnosis, and the bond graph modeling language has proved to be helpful for this task. In this paper we present an algorithm for automatically derive ARR-like structures, possible conflicts, from the bond graph model of a system. The algorithm uses temporal causal graphs as an intermediate structure to generate the set of possi...

Contraptions for intrauterine contraception.

©FSRH J Fam Plann Reprod Health Care 2008: 34(3) Summary Intrauterine contraception is underutilised largely due to its reputed association with infections. The Copper T-380A, one of the most cost-effective methods of contraception and the most widely used intrauterine contraceptive device in the world, is effective for at least 12 years and is also used for emergency contraception. The levonor...

On designing heteroclinic networks from graphs

Robust heteroclinic networks are invariant sets that can appear as attractors in symmetrically coupled or otherwise constrained dynamical systems. These networks may have a complicated structure determined to a large extent by the constraints and dimension of the system. As these networks are of great interest as dynamical models of biological and cognitive processes, it is useful to understand...