\begin{table*}[!ht]
\caption{Description of Benchmarks}
\label{tab:benchmarks}
\centering
\fontsize{7.8}{9.36}\selectfont
\setlength\tabcolsep{2pt}
\begin{tabular}{r|lp{9.5cm}|rr|rr}
\toprule
Prog &                        Name &                                                                                          Description &    \#Param &     \#Data &   ADVI &   NUTS \\
\midrule
RA  &   anova\_radon\_nopred\_chr &   Multi-level linear model with set up for ANOVA with Choo-Hoffman Parametrization &   88 &   919 &   10.38 &    20.28 \\
RE  &             electric\_chr &  Multi-level linear model with varying intercept with Choo-Hoffman Parametrization &  100 &   192 &    5.65 &    12.57 \\
RG  &    flight\_simulator\_17.3 &                                                            Varying intercept model &   17 &   281 &    4.25 &    12.28 \\
RK  &                      hiv &                          Multi-level linear model with varying slope and intercept &  173 &   369 &    7.00 &    20.33 \\
RL  &               lightspeed &                                                    Linear model with no predictors &    2 &    66 &    0.68 &     0.69 \\
RN  &                   pilots &     Multi-level linear model with varying intercept and redundant parameterization &   17 &    40 &    1.57 &     3.17 \\
RQ  &            radon\_no\_pool &                                           Multi-level linear model without pooling &   89 &   919 &   12.64 &    13.60 \\
RR  &            radon.pooling &                                     Multi-level linear model with complete pooling &    3 &   919 &    7.18 &     5.53 \\
RU  &            radon\_vary\_si &                               Multi-level linear model with group level predictors &  175 &   919 &   14.77 &    33.95 \\
RV  &             unemployment &                                                    Linear model with one predictor &    3 &    57 &    0.48 &     1.46 \\
RW  &                wells\_dae &                                                        Logitistic regression model &    4 &  3020 &   14.06 &   113.85 \\
RX  &                      y\_x &                                                    Linear model with one predictor &    3 &   919 &    7.93 &     9.17 \\
RY  &         kidscore\_momwork &                                               Linear model with discrete predictor &    5 &   434 &    3.98 &     9.26 \\
SA &            gp-fit-latent &  Gaussian process (GP) with exponentiated quadratic kernel and Gaussian likelihood &  104 &   101 &  150.63 &   732.07 \\
SB &    stochastic-volatility &                                               Moving average model for time-series &  503 &   500 &   11.52 &   170.22 \\
SC &              gp-fit-pois &                      GP with exponentiated quadratic kernel and Poisson likelihood &  104 &   101 &  108.98 &   697.92 \\
SD &               gp-fit-ARD &   GP with ARD-parameterized exponentiated quadratic kernel and Gaussian likelihood &  105 &   101 &  141.25 &  1188.97 \\
SE &                    koyck &                                                          Geometric lag time-series &    4 &   200 &    1.88 &     6.61 \\
MA &    normal\_mixture\_k\_prop &                 Mixture model with unknown locations, scales and mixing proportion &   11 &  1000 &    9.98 &   601.02 \\
MB &         normal\_mixture\_k &                 Mixture model with unknown locations, scales and mixing proportion &    9 &  1000 &    1.98 &    80.11 \\
MC &           normal\_mixture &                                                     Mixture model with known scale &    3 &  1000 &   25.49 &    27.91 \\
MD &     gauss\_mix\_asym\_prior &                                         Mixture model with non-exchangeable priors &    5 &   100 &    1.75 &     3.28 \\
ME &    gauss\_mix\_given\_theta &                                         Mixture model with known mixing proportion &    4 &  1000 &   19.81 &    54.51 \\
MF &  gauss\_mix\_ordered\_prior &                                                  Mixture model with ordered priors &    5 &  1000 &   14.08 &    30.30 \\
\bottomrule
\end{tabular}
\vspace{-0.00in}
\end{table*}
