836 citations
- Herzberg Institute of AstrophysicsCA18 papers
- Macquarie UniversityAU17 papers
- University of California, BerkeleyUS14 papers
- Centre for Quantum Computation and Communication TechnologyAU13 papers
- National Astronomical ObservatoriesCN12 papers
- University of TorontoCA11 papers
- Australia Telescope National FacilityAU10 papers
- The University of SydneyAU10 papers
- University of British ColumbiaCA10 papers
- Commonwealth Scientific and Industrial Research OrganisationAU9 papers
- National Radio Astronomy ObservatoryUS7 papers
- The University of TokyoJP7 papers
6 papers · 1 filter
Maximal Information Transfer and Behavior Diversity in Random Threshold Networks
M. Andrecut, D. Foster, H. Carteret +1
Random Threshold Networks (RTNs) are an idealized model of diluted, non symmetric spin glasses, neural networks or gene regulatory networks. RTNs also serve as an interesting gener…
Parallel GPU Implementation of Iterative PCA Algorithms
M. Andrecut
Principal component analysis (PCA) is a key statistical technique for multivariate data analysis. For large data sets the common approach to PCA computation is based on the standar…
MIC: Mutual Information based hierarchical Clustering
Alexander Kraskov, Peter Grassberger
Clustering is a concept used in a huge variety of applications. We review a conceptually very simple algorithm for hierarchical clustering called in the following the {\it mutual i…
Fast GPU Implementation of Sparse Signal Recovery from Random Projections
M. Andrecut
We consider the problem of sparse signal recovery from a small number of random projections (measurements). This is a well known NP-hard to solve combinatorial optimization problem…
Mean Field Model of Genetic Regulatory Networks
M. Andrecut, S. A. Kauffman
In this paper, we propose a mean-field model which attempts to bridge the gap between random Boolean networks and more realistic stochastic modeling of genetic regulatory networks.…
Subgraph Ensembles and Motif Discovery Using a New Heuristic for Graph Isomorphism
Kim Baskerville, Maya Paczuski
A new heuristic based on vertex invariants is developed to rapidly distinguish non-isomorphic graphs to a desired level of accuracy. The method is applied to sample subgraphs from…