Imaging Intracellular Fluorescent Proteins at Nanometer Resolution
We introduce a method for optically imaging intracellular proteins at nanometer spatial resolution. Numerous sparse subsets of photoactivatable fluorescent protein molecules wer...
Publications
Explore 387 academic publications
Showing 12 of
387 publications
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization.
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative grad...
Principal component analysis: a review and recent developments
Large datasets are increasingly common and are often difficult to interpret. Principal component analysis (PCA) is a technique for reducing the dimensionality of such datasets, ...
DeepWalk
We present DeepWalk, a novel approach for learning latent representations of\nvertices in a network. These latent representations encode social relations in\na continuous vector...
Stable isotopes in precipitation
In chapter 2 the isotopic fractionation of water in some simple condensation-evaporation processes are considered quantitatively on the basis of the fractionation factors given ...
Independent Component Analysis
In this chapter, we discuss a statistical generative model called independent component analysis. It is basically a proper probabilistic formulation of the ideas underpinning sp...
Soil Carbon Sequestration Impacts on Global Climate Change and Food Security
The carbon sink capacity of the world's agricultural and degraded soils is 50 to 66% of the historic carbon loss of 42 to 78 gigatons of carbon. The rate of soil organic carbon ...
Ideal spatial adaptation by wavelet shrinkage
SUMMARY With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, ...
Canu: scalable and accurate long-read assembly via adaptive <i>k</i> -mer weighting and repeat separation
Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relativ...
Numerical Methods for Unconstrained Optimization and Nonlinear Equations
Preface 1. Introduction. Problems to be considered Characteristics of 'real-world' problems Finite-precision arithmetic and measurement of error Exercises 2. Nonlinear Problems ...
Deep Learning Face Attributes in the Wild
Predicting face attributes in the wild is challenging due to complex face variations. We propose a novel deep learning framework for attribute prediction in the wild. It cascade...
Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
The Nelder--Mead simplex algorithm, first published in 1965, is an enormously popular direct search method for multidimensional unconstrained minimization. Despite its widesprea...