output
20022015
most citedCold streams in early massive hot haloes as the main mode of galaxy formation

1.7k citations

Showing 2013Show all

21 papers · 1 filter

stat.ML20134 cited

Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension

Hamed Firouzi, Bala Rajaratnam, Alfred Hero

We introduce a new approach to variable selection, called Predictive Correlation Screening, for predictor design. Predictive Correlation Screening (PCS) implements false positive c…

cond-mat.mes-hall201336 cited

Crossover from adiabatic to antiadiabatic phonon-assisted tunneling in single-molecule transistors

Eitan Eidelstein, Dotan Goberman, Avraham Schiller

The crossover between two customary limits of phonon-assisted tunneling, the adiabatic and antiadiabatic regimes, is studied systematically in the framework of a minimal model for…

nucl-th201325 cited

Partial dynamical symmetry as a selection criterion for many-body interactions

A. Leviatan, J. E. Garcia-Ramos, P. Van Isacker

We propose the use of partial dynamical symmetry (PDS) as a selection criterion for higher-order terms in situations when a prescribed symmetry is obeyed by some states and is stro…

physics.soc-ph201318 cited

The transition towards immortality: non-linear autocatalytic growth of citations to scientific papers

Michael Golosovsky, Sorin Solomon

We discuss microscopic mechanisms of complex network growth, with the special emphasis of how these mechanisms can be evaluated from the measurements on real networks. As an exampl…

physics.optics20139 cited

Rapidly reconfigurable optically induced photonic crystals in hot rubidium vapor

Bethany Little, David J. Starling, John C. Howell +3

Through periodic index modulation, we create two different types of photonic structures in a heated rubidium vapor for controlled reflection, transmission and diffraction of light.…

cs.LG201318 cited

Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm

Nir Friedman, Iftach Nachman, Dana Pe'er

Learning Bayesian networks is often cast as an optimization problem, where the computational task is to find a structure that maximizes a statistically motivated score. By and larg…