diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt
index a43c8aa..9959563 100644
--- a/examples/CMakeLists.txt
+++ b/examples/CMakeLists.txt
@@ -76,6 +76,12 @@
 add_executable(simple_bundle_adjuster simple_bundle_adjuster.cc)
 target_link_libraries(simple_bundle_adjuster Ceres::ceres)
 
+add_executable(bicubic_interpolation bicubic_interpolation.cc)
+target_link_libraries(bicubic_interpolation Ceres::ceres)
+
+add_executable(bicubic_interpolation_analytic bicubic_interpolation_analytic.cc)
+target_link_libraries(bicubic_interpolation_analytic Ceres::ceres)
+
 if (GFLAGS)
   add_executable(powell powell.cc)
   target_link_libraries(powell Ceres::ceres gflags)
diff --git a/examples/bicubic_interpolation.cc b/examples/bicubic_interpolation.cc
new file mode 100644
index 0000000..f097436
--- /dev/null
+++ b/examples/bicubic_interpolation.cc
@@ -0,0 +1,153 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2021 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Bicubic interpolation with automatic differentiation
+//
+// We will use estimation of 2d shift as a sample problem for bicubic
+// interpolation.
+//
+// Let us define f(x, y) = x * x - y * x + y * y
+// And optimize cost function sum_i [f(x_i + s_x, y_i + s_y) - v_i]^2
+//
+// Bicubic interpolation of f(x, y) will be exact, thus we can expect close to
+// perfect convergence
+
+#include "ceres/ceres.h"
+#include "ceres/cubic_interpolation.h"
+#include "glog/logging.h"
+
+using Grid = ceres::Grid2D<double>;
+using Interpolator = ceres::BiCubicInterpolator<Grid>;
+
+// Cost-function using autodiff interface of BiCubicInterpolator
+struct AutoDiffBiCubicCost {
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
+
+  template <typename T>
+  bool operator()(const T* s, T* residual) const {
+    using Vector2T = Eigen::Matrix<T, 2, 1>;
+    Eigen::Map<const Vector2T> shift(s);
+
+    const Vector2T point = point_ + shift;
+
+    T v;
+    interpolator_.Evaluate(point.y(), point.x(), &v);
+
+    *residual = v - value_;
+    return true;
+  }
+
+  AutoDiffBiCubicCost(const Interpolator& interpolator,
+                      const Eigen::Vector2d& point,
+                      double value)
+      : point_(point), value_(value), interpolator_(interpolator) {}
+
+  static ceres::CostFunction* Create(const Interpolator& interpolator,
+                                     const Eigen::Vector2d& point,
+                                     double value) {
+    return new ceres::AutoDiffCostFunction<AutoDiffBiCubicCost, 1, 2>(
+        new AutoDiffBiCubicCost(interpolator, point, value));
+  }
+
+  const Eigen::Vector2d point_;
+  const double value_;
+  const Interpolator& interpolator_;
+};
+
+// Function for input data generation
+static double f(const double& x, const double& y) {
+  return x * x - y * x + y * y;
+}
+
+int main(int argc, char** argv) {
+  google::InitGoogleLogging(argv[0]);
+  // Problem sizes
+  const int kGridRowsHalf = 9;
+  const int kGridColsHalf = 11;
+  const int kGridRows = 2 * kGridRowsHalf + 1;
+  const int kGridCols = 2 * kGridColsHalf + 1;
+  const int kPoints = 4;
+
+  const Eigen::Vector2d shift(1.234, 2.345);
+  const std::array<Eigen::Vector2d, kPoints> points = {
+      Eigen::Vector2d{-2., -3.},
+      Eigen::Vector2d{-2., 3.},
+      Eigen::Vector2d{2., 3.},
+      Eigen::Vector2d{2., -3.}};
+
+  // Data is a row-major array of kGridRows x kGridCols values of function
+  // f(x, y) on the grid, with x in {-kGridColsHalf, ..., +kGridColsHalf},
+  // and y in {-kGridRowsHalf, ..., +kGridRowsHalf}
+  double data[kGridRows * kGridCols];
+  for (int i = 0; i < kGridRows; ++i) {
+    for (int j = 0; j < kGridCols; ++j) {
+      // Using row-major order
+      int index = i * kGridCols + j;
+      double y = i - kGridRowsHalf;
+      double x = j - kGridColsHalf;
+
+      data[index] = f(x, y);
+    }
+  }
+  const Grid grid(data,
+                  -kGridRowsHalf,
+                  kGridRowsHalf + 1,
+                  -kGridColsHalf,
+                  kGridColsHalf + 1);
+  const Interpolator interpolator(grid);
+
+  Eigen::Vector2d shift_estimate(3.1415, 1.337);
+
+  ceres::Problem problem;
+  problem.AddParameterBlock(shift_estimate.data(), 2);
+
+  for (const auto& p : points) {
+    const Eigen::Vector2d shifted = p + shift;
+
+    const double v = f(shifted.x(), shifted.y());
+    problem.AddResidualBlock(AutoDiffBiCubicCost::Create(interpolator, p, v),
+                             nullptr,
+                             shift_estimate.data());
+  }
+
+  ceres::Solver::Options options;
+  options.minimizer_progress_to_stdout = true;
+
+  ceres::Solver::Summary summary;
+  ceres::Solve(options, &problem, &summary);
+  std::cout << summary.BriefReport() << '\n';
+
+  std::cout << "Bicubic interpolation with automatic derivatives:\n";
+  std::cout << "Estimated shift: " << shift_estimate.transpose()
+            << ", ground-truth: " << shift.transpose()
+            << " (error: " << (shift_estimate - shift).transpose() << ")"
+            << std::endl;
+
+  CHECK_LT((shift_estimate - shift).norm(), 1e-9);
+  return 0;
+}
diff --git a/examples/bicubic_interpolation_analytic.cc b/examples/bicubic_interpolation_analytic.cc
new file mode 100644
index 0000000..84c99bb
--- /dev/null
+++ b/examples/bicubic_interpolation_analytic.cc
@@ -0,0 +1,164 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2021 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Bicubic interpolation with analytic differentiation
+//
+// We will use estimation of 2d shift as a sample problem for bicubic
+// interpolation.
+//
+// Let us define f(x, y) = x * x - y * x + y * y
+// And optimize cost function sum_i [f(x_i + s_x, y_i + s_y) - v_i]^2
+//
+// Bicubic interpolation of f(x, y) will be exact, thus we can expect close to
+// perfect convergence
+
+#include "ceres/ceres.h"
+#include "ceres/cubic_interpolation.h"
+#include "glog/logging.h"
+
+using Grid = ceres::Grid2D<double>;
+using Interpolator = ceres::BiCubicInterpolator<Grid>;
+
+// Cost-function using analytic interface of BiCubicInterpolator
+struct AnalyticBiCubicCost : public ceres::CostFunction {
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
+
+  bool Evaluate(double const* const* parameters,
+                double* residuals,
+                double** jacobians) const {
+    Eigen::Map<const Eigen::Vector2d> shift(parameters[0]);
+
+    const Eigen::Vector2d point = point_ + shift;
+
+    double* f = residuals;
+    double* dfdr = nullptr;
+    double* dfdc = nullptr;
+    if (jacobians && jacobians[0]) {
+      dfdc = jacobians[0];
+      dfdr = dfdc + 1;
+    }
+
+    interpolator_.Evaluate(point.y(), point.x(), f, dfdr, dfdc);
+
+    if (residuals) {
+      *f -= value_;
+    }
+    return true;
+  }
+
+  AnalyticBiCubicCost(const Interpolator& interpolator,
+                      const Eigen::Vector2d& point,
+                      double value)
+      : point_(point), value_(value), interpolator_(interpolator) {
+    set_num_residuals(1);
+    *mutable_parameter_block_sizes() = {2};
+  }
+
+  static ceres::CostFunction* Create(const Interpolator& interpolator,
+                                     const Eigen::Vector2d& point,
+                                     double value) {
+    return new AnalyticBiCubicCost(interpolator, point, value);
+  }
+
+  const Eigen::Vector2d point_;
+  const double value_;
+  const Interpolator& interpolator_;
+};
+
+// Function for input data generation
+static double f(const double& x, const double& y) {
+  return x * x - y * x + y * y;
+}
+
+int main(int argc, char** argv) {
+  google::InitGoogleLogging(argv[0]);
+  // Problem sizes
+  const int kGridRowsHalf = 9;
+  const int kGridColsHalf = 11;
+  const int kGridRows = 2 * kGridRowsHalf + 1;
+  const int kGridCols = 2 * kGridColsHalf + 1;
+  const int kPoints = 4;
+
+  const Eigen::Vector2d shift(1.234, 2.345);
+  const std::array<Eigen::Vector2d, kPoints> points = {
+      Eigen::Vector2d{-2., -3.},
+      Eigen::Vector2d{-2., 3.},
+      Eigen::Vector2d{2., 3.},
+      Eigen::Vector2d{2., -3.}};
+
+  // Data is a row-major array of kGridRows x kGridCols values of function
+  // f(x, y) on the grid, with x in {-kGridColsHalf, ..., +kGridColsHalf},
+  // and y in {-kGridRowsHalf, ..., +kGridRowsHalf}
+  double data[kGridRows * kGridCols];
+  for (int i = 0; i < kGridRows; ++i) {
+    for (int j = 0; j < kGridCols; ++j) {
+      // Using row-major order
+      int index = i * kGridCols + j;
+      double y = i - kGridRowsHalf;
+      double x = j - kGridColsHalf;
+
+      data[index] = f(x, y);
+    }
+  }
+  const Grid grid(data,
+                  -kGridRowsHalf,
+                  kGridRowsHalf + 1,
+                  -kGridColsHalf,
+                  kGridColsHalf + 1);
+  const Interpolator interpolator(grid);
+
+  Eigen::Vector2d shift_estimate(3.1415, 1.337);
+
+  ceres::Problem problem;
+  problem.AddParameterBlock(shift_estimate.data(), 2);
+
+  for (const auto& p : points) {
+    const Eigen::Vector2d shifted = p + shift;
+
+    const double v = f(shifted.x(), shifted.y());
+    problem.AddResidualBlock(AnalyticBiCubicCost::Create(interpolator, p, v),
+                             nullptr,
+                             shift_estimate.data());
+  }
+
+  ceres::Solver::Options options;
+  options.minimizer_progress_to_stdout = true;
+
+  ceres::Solver::Summary summary;
+  ceres::Solve(options, &problem, &summary);
+  std::cout << summary.BriefReport() << '\n';
+
+  std::cout << "Bicubic interpolation with analytic derivatives:\n";
+  std::cout << "Estimated shift: " << shift_estimate.transpose()
+            << ", ground-truth: " << shift.transpose()
+            << " (error: " << (shift_estimate - shift).transpose() << ")"
+            << std::endl;
+
+  CHECK_LT((shift_estimate - shift).norm(), 1e-9);
+  return 0;
+}