diff --git a/experiments/resnet_best_results_to_latex.py b/experiments/resnet_best_results_to_latex.py
new file mode 100644
index 0000000..c9d4f77
--- /dev/null
+++ b/experiments/resnet_best_results_to_latex.py
@@ -0,0 +1,39 @@
+"""Simple script to make a latex table from resnet results"""
+
+import pandas as pd
+
+df = pd.read_csv("results/resnet101_only/best_results-conv-cpu-usage_stats.csv")
+df = df.set_index("model")
+df = df.drop(columns=["Scaled M", "Scaled T"])
+df = df.drop("memsave_resnet101_conv+relu+bn")
+df = df[df["case"] != "SurgicalLast"]
+df = df[df["case"] != "Conv"]
+
+mem_div = df[df["case"] == "All"].loc["resnet101", "Memory Usage (GB)"]
+time_div = df[df["case"] == "All"].loc["resnet101", "Time Taken (s)"]
+df["Scaled M"] = df["Memory Usage (GB)"] / mem_div
+df["Scaled T"] = df["Time Taken (s)"] / time_div
+
+df["Memory [GiB]"] = df.apply(
+    lambda x: f"{x['Memory Usage (GB)']:.2f} ({x['Scaled M']:.2f})", axis=1
+)
+df["Time [s]"] = df.apply(
+    lambda x: f"{x['Time Taken (s)']:.2f} ({x['Scaled T']:.2f})", axis=1
+)
+
+df = df.drop(columns=["Scaled M", "Scaled T", "Memory Usage (GB)", "Time Taken (s)"])
+df_p = df.pivot_table(
+    index="model", columns="case", values=df.columns[1:], aggfunc=lambda x: x
+)
+
+labels = {
+    "resnet101": "Default ResNet-101",
+    "memsave_resnet101_conv": "+ swap Convolution",
+    "memsave_resnet101_conv_full": "+ swap BatchNorm, ReLU",
+}
+
+df_p = df_p.rename(index=labels)
+df_p = df_p.sort_index(ascending=False)
+
+print(df_p["Memory [GiB]"].to_latex())
+print(df_p["Time [s]"].to_latex())