Update app.py

app.py

@@ -3,7 +3,29 @@ import streamlit as st
 import matplotlib.pyplot as plt
 
 st.subheader("Gaussian Process Regression")
-st_col = st.columns(1)[0]
+st_cols = st.columns(2)
+st_col = st_cols[0]
+
+st_col_text = st_cols[1]
+
+st_col_text.latex("""
+        \\text{{Gamma}}(
+            \\tau
+            ;
+            \\alpha
+            ,
+            \\beta
+        )
+        =
+        \\frac{{
+            \\beta^{{\\alpha}}
+        }} {{
+            \\Gamma(\\alpha)
+        }}
+        \\tau^{{\\alpha - 1}}
+        e^{{-\\beta \\tau}}
+    """)
+
 
 lengthscale = st.slider('Lengthscale', min_value=0.01, max_value=1.0, value=0.25, step=0.01)
 variance = st.slider('Variance', min_value=0.001, max_value=0.1, value=0.025, step=0.001)