diff --git a/src/Numerics/Interpolate.cs b/src/Numerics/Interpolate.cs
index cc2ec45e..50db7a0d 100644
--- a/src/Numerics/Interpolate.cs
+++ b/src/Numerics/Interpolate.cs
@@ -102,6 +102,23 @@ namespace MathNet.Numerics
             return Interpolation.Barycentric.InterpolatePolynomialEquidistant(points, values);
         }
 
+        /// <summary>
+        /// Create a neville polynomial interpolation based on arbitrary points.
+        /// If the points happen to be equidistant, consider to use the much more robust PolynomialEquidistant instead.
+        /// Otherwise, consider whether RationalWithoutPoles would not be a more robust alternative.
+        /// </summary>
+        /// <param name="points">The sample points t. Supports both lists and arrays.</param>
+        /// <param name="values">The sample point values x(t). Supports both lists and arrays.</param>
+        /// <returns>
+        /// An interpolation scheme optimized for the given sample points and values,
+        /// which can then be used to compute interpolations and extrapolations
+        /// on arbitrary points.
+        /// </returns>
+        public static IInterpolation Polynomial(IList<double> points, IList<double> values)
+        {
+            return new NevillePolynomialInterpolation(points, values);
+        }
+
         /// <summary>
         /// Create a piecewise linear spline interpolation based on arbitrary points.
         /// </summary>
@@ -121,6 +138,25 @@ namespace MathNet.Numerics
             return Interpolation.LinearSpline.Interpolate(points, values);
         }
 
+        /// <summary>
+        /// Create an piecewise cubic spline interpolation based on arbitrary points, with zero secondary derivatives at the boundaries.
+        /// </summary>
+        /// <param name="points">The sample points t. Optimized for arrays.</param>
+        /// <param name="values">The sample point values x(t). Optimized for arrays.</param>
+        /// <returns>
+        /// An interpolation scheme optimized for the given sample points and values,
+        /// which can then be used to compute interpolations and extrapolations
+        /// on arbitrary points.
+        /// </returns>
+        /// <remarks>
+        /// The value pairs do not have to be sorted, but if they are not sorted ascendingly
+        /// and the passed x and y arguments are arrays, they will be sorted inplace and thus modified.
+        /// </remarks>
+        public static IInterpolation CubicSpline(IEnumerable<double> points, IEnumerable<double> values)
+        {
+            return Interpolation.CubicSpline.Interpolate(points, values);
+        }
+
         /// <summary>
         /// Create an piecewise cubic Akima spline interpolation based on arbitrary points. Akima splines are robust to outliers.
         /// </summary>