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K. Law

65 papers hereh-index 293.4k citations114 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author14
  • middle author43
  • last author6

Across the 64 of 65 papers where every author was matched, so the position is known.

fields
  • stat.CO16
  • nlin.PS9
  • math.NA8
  • math.PR6
  • math.DS3
  • math.OC3
same name
  • K. Law — 13 papers, h 11
  • K. Law — 8 papers, h 3
  • K. Law — 6 papers, h 51
  • K. Law — 2 papers, h 2
  • K. Law — 2 papers, h 6
  • K. Law — 2 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20082022
most citedThe Ensemble Kalman Filter for Inverse Problems

447 citations · 2.5k across the 63 of their papers we have counts for

collaborators
Showing 2013Show all

3 papers · 1 filter

math.PR2013★ 119 cited

Well-Posedness And Accuracy Of The Ensemble Kalman Filter In Discrete And Continuous Time

D. T. B. Kelly, K. J. H. Law, A. M. Stuart

The ensemble Kalman filter (EnKF) is a method for combining a dynamical model with data in a sequential fashion. Despite its widespread use, there has been little analysis of its t…

math.PR2013★ 162 cited

MAP Estimators and Their Consistency in Bayesian Nonparametric Inverse Problems

Masoumeh Dashti, Kody J. H. Law, Andrew M. Stuart +1

We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map G applied to u. We adopt a Bayes…

math.PR2013

Determining White Noise Forcing From Eulerian Observations in the Navier Stokes Equation

Viet Ha Hoang, Kody J. H. Law, Andrew M. Stuart

The Bayesian approach to inverse problems is of paramount importance in quantifying uncertainty about the input to and the state of a system of interest given noisy observations. H…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.