\noindent
{\sc Barron, A., Schervish, M. and Wasserman, L.} (1999).
The consistency of posterior distributions in 
nonparametric problems.
{\em The Annals of Statistics}, 
{27}, 536-561.

\noindent
{\sc Bryan, B., Schneider, J., Miller, C., Nichol, R.,
Genovese, C. and Wasserman, L.} (2007).  
Mapping the Cosmological Confidence Ball Surface 
{\em Astrophysical Journal},
{\bf 665}, p. 25.

\noindent
{\sc Chan, N. H. and Genovese, C. R.} (2001).
A Comparison of Linear and Nonlinear Statistical
Techniques in Performance Attribution,
{\em IEEE Transactions on Neural Networks},
special issue on Neural Networks in Financial Engineering,
{12}, 922--928.

\noindent 
{\sc Connolly, A.J, Nichol, A.J., Moore, A.W.,
Schneider, J., Genovese, C. and Wasserman, L.} (2000).
Fast Algorithms and Efficient Statistics: Density Estimation in Large Astronomical
Datasets.
{\em The Astrophysics Journal}.

\noindent 
{\sc Connolly, A., Moore, A., Miller, C., 
Genovese, C., Nichol, R. and Wasserman, L.} (2002).
Nonparametric statistics in astrophysics.
In {\em Statistical Challenges in Modern Astronomy III.}
Eric D. Feigelson and G. Jogesh Babu (eds.)
New York: Springer-Verlag.

\noindent
{\sc DiMatteo, I., Genovese, C. R., and Kass, R. E.} (2001).
Bayesian curve-fitting with free-knot splines,
{\em Biometrika}, {88}, 1055--1071.

\noindent
{\sc Eddy, W. F., Fitzgerald, M., Genovese, C. R., Lazar, N., Mockus, A., and Welling, J.} (1999).
The Challenge of Functional Magnetic Resonance Imaging,
{\em Journal of Computational and Graphical Statistics}, {8}, 545--558.

\noindent
{\sc Freeman, P.E., Genovese, C.R., Miller, C.J., Nichol, R.C. and
Wasserman, L.} (2006).
Examining the Effect of the Map-Making Algorithm on Observed Power
Asymmetry in WMAP Data.
{\em The Astrophysical Journal}, v.~638,
pp.~1-19.

\noindent
{\sc Genovese, C. R.} (2000). 
A Bayesian Time-Course Model for Functional Magnetic Resonance Imaging Data (with discussion),
{\em Journal of the American Statistical Association}, {95}, % No. 451,
691--703.
[Selected as the JASA Applications and Case Studies Invited Paper for 2000.]

\noindent
{\sc Genovese, C.R., Freeman, P., Wasserman, L., Nichol, R., and Miller, C.} (2009).
Inference for the Dark Energy Equation of State using Type Ia
Supernova Data,
{\em Annals Appl. Stats.}, {\bf 3}, 144--178.

\noindent
{\sc Genovese, C.R., Lazar, N.A. and Nichols, T.E.} (2002)
Thresholding of statistical maps in functional
neuroimaging using the false discovery rate. 
{\it NeuroImage}, {15}, 870--878.

\noindent
{\sc Genovese, C.~R., Roeder, K., and Wasserman, L.}~(2006).
False Discovery Control with P-value Weighting
\emph{Biometrika}, 
{93}(3), 509--524.

\noindent {\sc Genovese, C. and Wasserman, L.} (2000).
Rates of Convergence for the Gaussian Mixture Sieve
{\em Annals of Statistics}, {28}, 1105-1127.

\noindent 
{\sc Genovese, C. and Wasserman, L.} (2002).
Operating Characteristics and Extensions of the FDR Procedure .
{\em J. Roy. Statist., Soc. B}, {64}, 499-518.

\noindent 
{\sc Genovese, C. and Wasserman, L.} (2002).
Bayesian and Frequentist Multiple Testing.
{\em Valencia VI}.

\noindent 
{\sc Genovese, C. and Wasserman, L.} (2004).
A stochastic process approach to false
discovery rates.
{\em Ann. of Statist.}, {32}, 1035--1061.

\noindent 
{\sc Genovese, C. and Wasserman, L.} (2005).
Confidence Sets for Nonparametric Wavelet 
Regression.
\emph{Ann. of Statist.},  Ann. Statist.  {33}, 698--729.

\noindent
{\sc Genovese, C. and Wasserman, L.} (2006).
Exceedance Control of the False Discovery Proportion.
{\em Journal of the American Statistical Association}, 101, 1408--1417.

\noindent
{\sc Genovese, C. and Waserman, L.} (2007)
Adaptive confidence bands.
{\em Annals Stats.}, {\bf 38}, 875--905, (2008).

\noindent 
{\sc Genovese, C., Miller, C., Nichol, R. Arjunwadkar, M. and Wasserman, L.} (2004).
Nonparametric Inference for the Cosmic Microwave Background.
\emph{Statistical Science}, {19}, 308--321.
[Winner of the American Statistical Association Outstanding Statistical Application Award for 2005.]

\noindent
{\sc Genovese, C. R. and Sweeney, J. A.} (1999).
Functional Connectivity in the Cortical Regions Subserving Eye Movements (with discussion),
in {\em Case Studies in Bayesian Statistics}, Volume 4, 
eds. R. E. Kass, B. P. Carlin, A. L. Carriquiry, C. Gatsonis,
A. Gelman, I. Verdinelli, and M. West,  Springer Verlag, pp. 59--132.

\noindent
{\sc Goddard, N. H., Hood, G., Cohen, J. D.,
Nystrom, L. E., Eddy, W. F., Genovese, C. R.,
and Noll, D. C.} (2000).
Functional Magnetic Resonance Imaging Dataset Analysis,
in 
{\em Industrial Strength Parallel Computing},
ed. A. Koniges,
Morgan Kaufman Publishers, New York, 431--451.


\noindent 
{\sc Hoskins, A., Miller, C.,} 
{\sc Connolly, A., Genovese, C., Nichol, R. and Wasserman, L.} (2002).
A new source detection algorithm using FDR.
{\em The Astronomical Journal}.
123, 1086-1094.

\noindent
{\sc Lazar, N. A., Eddy, W. F., Genovese, C. R. and Welling, J.} (2001).
Statistical Issues in fMRI for Brain Imaging,
{\em International Statistical Review}, {69}, 105--127.

\noindent
{\sc Luna, B., Thulborn, K. R., Munoz, D. P., Merriam, E. P., Garver, 
K. E., Minshew, N. J., Keshavan, M. S., Genovese, C. R., Eddy, 
W. F., and Sweeney, J. A.} (2001). Maturation of widely distributed 
brain function subserves cognitive development. {\em Neuroimage}, 13(5), 
786-793.

\noindent
{\sc Marotta, J.J., Genovese, C.R., and Behrmann, M.}  (2001).  A functional MRI
study of face recognition in patients with prosopagnosia.  {\em Neuroreport},
12(8), 1581-1587.

\noindent
{\sc Merriam, E.P., Genovese, C.R., and Colby, C.L.}~(2003).
Spatial Updating in Human Parietal Cortex,
\emph{Neuron}, {39}, 361--373


\noindent
{\sc Miller, C., Nichol, R., and Batuski, D.} (2001).
 Matter and Temperature Fluctuations in the Early Universe and Today
 {\em Science}, {292}, 3202-3203.

\noindent
{\sc Miller, C., Nichol, R., and Batuski, D.} (2001).
 Possible Detection of Baryonic Fluctuations in the Large Scale Structure
Power Spectrum
 {\em Astrophys. J.}, {555}, 68-74.

\noindent
{\sc Miller, C., Nichol, R., and Chen, X.} (2002).
 Detecting the Baryons in Matter Power Spectra
 {\em Astrophys. J.}, {579}, 483-490.

\noindent 
{\sc Miller, C., Genovese, C. Nichol, R., Wasserman, L., Connolly, A., 
Reichart, D., Hopkins, A., Schneider, J., Moore, A.} (2001).
Controlling the False Discovery Rate in Astrophysical Data Analysis.
{\em The Astronomical Journal.}
122, 2492-3505.

\noindent 
{\sc Miller, Christopher J.; Nichol, Robert C.;
Genovese, Christopher; Wasserman, Larry} (2002).
A Nonparametric Analysis of the Cosmic Microwave
Background Power Spectrum.
{\em The Astrophysical Journal}, {565L}, Issue 2, pp. L67-L70.

\noindent 
{\sc Moore, A., Connolly, A., Genovese, C., Gray, A.,
Grone, L., Kanidoris, N. Nichol, R. Schneider, J. Szalay, A. Szapudi, I.,
Wasserman, L.} (2000).
Fast Algorithms and Efficient Statistics: N-point Correlation Functions
{\em Proceedings of MPA/MPE/ESO 
Conference "Mining the Sky", July 31 - August 4, 2000,
Garching, Germany.}

\noindent
{\sc Perone Pacifico, M, Genovese, C, Verdinelli, I., Wasserman, L.} (2004).
False Discovery Rates for Random Fields.
{\em Journal of the American Statistical Association}, 99, 1002--1014.

\noindent
{\sc Perone Pacifico, M, Genovese, C, Verdinelli, I., Wasserman, L.} (2007).
Scan Clustering: A False Discovery Approach.
{\em Journal of Multivariate Analysis},
{98}, 1441--1469.

\noindent
{\sc Perone Pacifico, M, Genovese, C, Verdinelli, I., Wasserman, L.} (2009).
Inference for the Dark Energy Equation of State using Type Ia
Supernova Data,
{\em Ann. Stat.}, {\bf 37}, 3236--3271.

\noindent 
{\sc Petrone, S. and Wasserman, L.} (2002).
Consistency of Bernstein Polynomial Posteriors.
{\em J. Roy. Statist., Soc. B}. 64, 79-100.

\noindent 
{\sc Shen, X. and Wasserman, L.} (2001).
Rates of Convergence of Posterior Distributions.
{\em The Annals of Statistics}, {29}, 687-714.


\noindent 
{\sc Wasserman, L.} (2000).
Asymptotic Inference for Mixture Models Using Data Dependent Priors.
{\em J. Roy. Statist., Soc. B}, {62}, 159-180.


\noindent 
{\sc Wasserman, L.} (2000).
Bayesian Model Selection and Model Averaging.
{\em Journal of Mathematical Psychology}, {44},
92-107.
