diff --git a/vortex-filtering/include/vortex_filtering/filters/ukf.hpp b/vortex-filtering/include/vortex_filtering/filters/ukf.hpp
index 8fb51c6e..f39b4a00 100644
--- a/vortex-filtering/include/vortex_filtering/filters/ukf.hpp
+++ b/vortex-filtering/include/vortex_filtering/filters/ukf.hpp
@@ -66,11 +66,11 @@ template <models::concepts::DynamicModel DynModT, models::concepts::SensorModel
   using Gauss_x = prob::MultiVarGauss<N_DIM_x>;
   using Gauss_z = prob::MultiVarGauss<N_DIM_z>;
 
-  static constexpr int N_DIM_a = N_DIM_x + N_DIM_v + N_DIM_w; // Augmented state dimension
-  static constexpr size_t N_SIGMA_POINTS = 2 * N_DIM_a + 1;   // Number of sigma points
+  static constexpr int N_DIM_a           = N_DIM_x + N_DIM_v + N_DIM_w; // Augmented state dimension
+  static constexpr size_t N_SIGMA_POINTS = 2 * N_DIM_a + 1;             // Number of sigma points
 
-  using Vec_a     = Eigen::Vector<double, N_DIM_a>;                  // Augmented state vector
-  using Mat_aa    = Eigen::Matrix<double, N_DIM_a, N_DIM_a>;         // Augmented state covariance matrix
+  using Vec_a     = Eigen::Vector<double, N_DIM_a>;                 // Augmented state vector
+  using Mat_aa    = Eigen::Matrix<double, N_DIM_a, N_DIM_a>;        // Augmented state covariance matrix
   using Mat_x2ap1 = Eigen::Matrix<double, N_DIM_x, N_SIGMA_POINTS>; // Matrix for sigma points of x
   using Mat_z2ap1 = Eigen::Matrix<double, N_DIM_z, N_SIGMA_POINTS>; // Matrix for sigma points of z
   using Mat_a2ap1 = Eigen::Matrix<double, N_DIM_a, N_SIGMA_POINTS>; // Matrix for sigma points of a
@@ -100,7 +100,6 @@ template <models::concepts::DynamicModel DynModT, models::concepts::SensorModel
     return W_c;
   }();
 
-
   UKF() = delete;
 
 private:
diff --git a/vortex-filtering/include/vortex_filtering/models/dynamic_model_interfaces.hpp b/vortex-filtering/include/vortex_filtering/models/dynamic_model_interfaces.hpp
index 53a3714d..fdcb1502 100644
--- a/vortex-filtering/include/vortex_filtering/models/dynamic_model_interfaces.hpp
+++ b/vortex-filtering/include/vortex_filtering/models/dynamic_model_interfaces.hpp
@@ -87,7 +87,6 @@ template <size_t n_dim_x, size_t n_dim_u = n_dim_x, size_t n_dim_v = n_dim_x> cl
     Gauss_v v = {Vec_v::Zero(), Q_d(dt, x)};
     return f_d(dt, x, u, v.sample(gen));
   }
-
 };
 
 /**
diff --git a/vortex-filtering/include/vortex_filtering/probability/poisson.hpp b/vortex-filtering/include/vortex_filtering/probability/poisson.hpp
index b38cb58f..493addf5 100644
--- a/vortex-filtering/include/vortex_filtering/probability/poisson.hpp
+++ b/vortex-filtering/include/vortex_filtering/probability/poisson.hpp
@@ -45,10 +45,7 @@ class Poisson {
    * @param x
    * @return double factorial
    */
-  static constexpr double factorial(int x)
-  {
-    return (x == 1 || x == 0) ? 1 : factorial(x - 1) * x;
-  }
+  static constexpr double factorial(int x) { return (x == 1 || x == 0) ? 1 : factorial(x - 1) * x; }
 };
 
 } // namespace vortex::prob