Non autregressive gru model load

Reports/Thesis/sections/results/gru.tex

@@ -30,15 +30,15 @@ Multiple experiments are conducted to find which hyperparameters and input featu
 \toprule
 Features & Layers & Hidden Size & \multicolumn{2}{c}{MSE} & \multicolumn{2}{c}{MAE} & \multicolumn{2}{c}{CRPS} \\ 
 \cmidrule(lr){4-5} \cmidrule(lr){6-7} \cmidrule(lr){8-9}
-& & & Train & Test & Train & Test & Train & Test \\
+& & & AR & NAR & AR & NAR & AR & NAR \\
 \midrule
 NRV & & & & & & & & \\
-& 2 & 256 & 34942.89 & 39838.35 & 142.43 & 150.81 & 81.34 & 85.04 \\
-& 4 & 256 & 34705.61 & 39506.55 & 141.74 & 149.81 & 81.89 & 85.46 \\
-& 8 & 256 & 32885.71 & 37747.11 & 138.16 & 146.67 & 79.99 & 83.67 \\ 
-& 2 & 512 & 35362.66 & 39955.79 & 143.19 & 150.77 & 84.37 & 87.88 \\
-& 4 & 512 & 38253.89 & 43301.13 & 148.33 & 156.73 & 85.98 & 89.78 \\
-& 8 & 512 & 33131.93 & 37681.71 & 138.93 & 146.62 & 79.64 & 83.08 \\
+& 2 & 256 & 39838.35 & 40097.62 & 150.81 & 150.37 & 85.04 & 76.12 \\
+& 4 & 256 & 39506.55 & 39968.96 & 149.81 & 150.04 & 85.46 & 76.07 \\
+& 8 & 256 & 37747.11 & 40400.37 & 146.67 & 151.03 & 83.67 & 76.59 \\ 
+& 2 & 512 & 39955.79 & 40917.24 & 150.77 & 152.04 & 87.88 & 76.06 \\
+& 4 & 512 & 43301.13 & 39954.62 & 156.73 & 150.14 & 89.78 & 76.25 \\
+& 8 & 512 & 37681.71 & 40379.14 & 146.62 & 151.05 & 83.08 & 76.42 \\
 \midrule
 NRV + Load & & & & & & & & & \\
 & 2 & 256 & 33202.80 & 38427.91 & 138.02 & 147.27 & 79.62 & 84.17 \\

Reports/Thesis/verslag.log

@@ -1,4 +1,4 @@
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