Network topology inference from incomplete observation data

Multi-model inference of network properties from incomplete data

It has previously been shown that subnets differ from global networks from which they are sampled for all but a very limited number of theoretical network models. These differences are of qualitative as well as quantitative nature, and the properties of subnets may be very different from the corresponding properties in the true, unobserved network. Here we propose a novel approach which allows ...

Image Reconstruction from Incomplete Data

Inference of Strategic Behavior based on Incomplete Observation Data

Inferring the goals, preferences and restrictions of strategically behaving agents is a common goal in many situations, and an important requirement for enabling computer systems to better model and understand human users. Inverse reinforcement learning (IRL) is one method for performing this kind of inference based on observations of the agent’s behavior. However, traditional IRL methods are o...

Image Reconstruction from Incomplete Data

Influence of Network Topology and Data Collection on Network Inference

We recently developed an approach for testing the accuracy of network inference algorithms by applying them to biologically realistic simulations with known network topology. Here, we seek to determine the degree to which the network topology and data sampling regime influence the ability of our Bayesian network inference algorithm, NETWORKINFERENCE, to recover gene regulatory networks. NETWORK...