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An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data.
Neutral two-locus multiple allele models with recombination
R. C. Griffiths · 1981
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The coalescent
J. F. C. Kingman · 1982
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Properties of a neutral allele model with intragenic recombination
R. R. Hudson · 1983
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Population growth of human Y chromosomes: a study of Y chromosome microsatellites
J K Pritchard, M T Seielstad, A Perez-Lezaun, and M W Feldman · 1999
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Meiotic recombination hot spots and cold spots
T. D. Petes · 2001
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Two-locus sampling distributions and their application
R. R. Hudson · 2001
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Approximate Bayesian computation in population genetics
M. A. Beaumont, W. Zhang, and D. J. Balding · 2002
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The international hapmap project
R. A. Gibbs, J. W. Belmont, P. Hardenbol, T. D. Willis, F. Yu, H. Yang, L.-Y. Ch’ang, W. Huang, B. Liu, Y. Shen, et al · 2003
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What’s so hot about recombination hotspots?
J. Hey · 2004
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The fine-scale structure of recombination rate variation in the human genome
G. A. T. McVean, S. R. Myers, S. Hunt, P. Deloukas, D. R. Bentley, and P. Donnelly · 2004
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Permutation invariant svms
P. K. Shivaswamy and T. Jebara · 2006
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SequenceLDhot: detecting recombination hotspots
P. Fearnhead · 2006
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A new method for detecting human recombination hotspots and its applications to the hapmap encode data
J. Li, M. Q. Zhang, and X. Zhang · 2006
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Efficient Approximate Bayesian Computation coupled with Markov chain Monte Carlo without likelihood
D. Wegmann, C. Leuenberger, and L. Excoffier · 2009
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Approximate Bayesian computation without summary statistics: The case of admixture
V. C. Sousa, M. Fritz, M. A. Beaumont, and L. Chikhi · 2009
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Population genomic inference of recombination rates and hotspots
Y. Wang and B. Rannala · 2009
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Searching for footprints of positive selection in whole-genome snp data from nonequilibrium populations
P. Pavlidis, J. D. Jensen, and W. Stephan · 2010
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Non-linear regression models for Approximate Bayesian Computation
MGB Blum and O François · 2010
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An asymptotic sampling formula for the coalescent with recombination
Inferring population size history from large samples of genome-wide molecular data-an approximate bayesian computation approach
S. Boitard, W. Rodríguez, F. Jay, S. Mona, and F. Austerlitz · 2016
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Fast ϵ \epsilon -free inference of simulation models with Bayesian conditional density estimation
G. Papamakarios and I. Murray · 2016
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Deep learning with sets and point clouds
S. Ravanbakhsh, J. Schneider, and B. Poczos · 2016
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Permutation-equivariant neural networks applied to dynamics prediction
N. Guttenberg, N. Virgo, O. Witkowski, H. Aoki, and R. Kanai · 2016
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Detecting recombination hotspots from patterns of linkage disequilibrium
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P. A. Jenkins and Y. S. Song · 2010
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Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation
P. Fearnhead and D. Prangle · 2012
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Rate of de novo mutations and the importance of father’s age to disease risk
A. Kong, M. L. Frigge, G. Masson, S. Besenbacher, P. Sulem, G. Magnusson, S. A. Gudjonsson, A. Sigurdsson, A. Jonasdottir, A. Jonasdottir, et al · 2012
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Identifying recombination hotspots using population genetic data
A. Auton, S. Myers, and G. McVean · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Inferring selective constraint from population genomic data suggests recent regulatory turnover in the human brain
D. R. Schrider and A. D. Kern · 2015
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Learning summary statistic for approximate Bayesian computation via deep neural network
B. Jiang, T.-y. Wu, C. Zheng, and W.H. Wong · 2015
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J. D. Wall and L. S. Stevison · 2016
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Efficient coalescent simulation and genealogical analysis for large sample sizes
J. Kelleher, A. M. Etheridge, and G. McVean · 2016
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Two-locus likelihoods under variable population size and fine-scale recombination rate estimation
J. A. Kamm, J. P. Spence, J. Chan, and Y. S. Song · 2016
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On calibration of modern neural networks
C. Guo, G. Pleiss, Y. Sun, and K. Q. Weinberger · 2017
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Deep sets
M. Zaheer, S. Kottur, S. Ravanbakhsh, B. Poczos, R. Salakhutdinov, and A. Smola · 2017
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Globally optimal gradient descent for a convnet with gaussian inputs
Alon Brutzkus and Amir Globerson · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
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The unreasonable effectiveness of convolutional neural networks in population genetic inference
Lex Flagel, Yaniv J Brandvain, and Daniel R Schrider · 2018
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Minimizing nonconvex population risk from rough empirical risk
Chi Jin, Lydia T Liu, Rong Ge, and Michael I Jordan · 2018
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