Background: RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily co...
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Existing work on programmable self assembly has focused on deterministic performance guarantees--stability of desirable states. In particular, for any acyclic target graph a binary...
Stochastic models such as hidden Markov models or stochastic context free grammars can fail to return the correct, maximum likelihood solution in the case of semantic ambiguity. T...
The paper studies the problem of distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and imperfect inter-sensor communication. We...