000167076 001__ 167076
000167076 005__ 20190316235146.0
000167076 037__ $$aSTUDENT
000167076 245__ $$aSpeeding up Markov Chain Monte Carlo without Likelihood
000167076 269__ $$a2010
000167076 260__ $$c2010
000167076 336__ $$aStudent Projects
000167076 520__ $$aThis article presents the implementation and initial test results for an algorithm called SuffStat MCMC, which aims to speed up Approximate Bayesian Computation without likelihood.
000167076 6531_ $$aApproximate Bayesian Computation
000167076 6531_ $$aMarkov Chain Monte Carlo
000167076 6531_ $$aComputational Biology
000167076 6531_ $$aPhylogenetics
000167076 700__ $$0(EPFLAUTH)176564$$aHelfer, Jonas$$g176564
000167076 720_2 $$aWegmann, Daniel$$edir.
000167076 720_2 $$0241987$$aMoret, Bernard$$edir.$$g172233
000167076 8564_ $$s392677$$uhttps://infoscience.epfl.ch/record/167076/files/ABC_MCMC_report.pdf$$yn/a$$zn/a
000167076 909C0 $$0252020$$pLCBB$$xU11274
000167076 909CO $$ooai:infoscience.tind.io:167076$$pIC$$qGLOBAL_SET
000167076 917Z8 $$x176564
000167076 937__ $$aEPFL-STUDENT-167076
000167076 973__ $$aEPFL$$sPUBLISHED
000167076 980__ $$aSTUDENT$$bSEMESTER