First poly(n,d,1/ε)-time algorithm for ε-approximate maximum-likelihood log-concave distribution estimation on n points in R^d.
Difficulties with inflationary cosmology
4 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
verdicts
UNVERDICTED 4roles
background 2polarities
background 2representative citing papers
The entropy of the sum of independent ternary random variables is maximized when the first n-1 variables are uniform on {0,2} and the nth follows a specific distribution defined by binomial entropies.
Rest-frame 6-8um MIRI luminosity provides broken power-law SFR calibrations with 0.2-0.3 dex scatter and UV+IR composites at 0.15 dex, supporting robust use above log M* ~9 up to z~3.
Lecture notes providing a generic introduction to reheating after inflation, covering its theoretical, phenomenological, and observational aspects.
citing papers explorer
-
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
First poly(n,d,1/ε)-time algorithm for ε-approximate maximum-likelihood log-concave distribution estimation on n points in R^d.
-
Maximum Entropy of Sums of Independent Ternary Random Variables
The entropy of the sum of independent ternary random variables is maximized when the first n-1 variables are uniform on {0,2} and the nth follows a specific distribution defined by binomial entropies.
-
Calibrating Photometric Mid-Infrared Star Formation Rates for JWST
Rest-frame 6-8um MIRI luminosity provides broken power-law SFR calibrations with 0.2-0.3 dex scatter and UV+IR composites at 0.15 dex, supporting robust use above log M* ~9 up to z~3.
-
Lectures on Reheating after Inflation
Lecture notes providing a generic introduction to reheating after inflation, covering its theoretical, phenomenological, and observational aspects.