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diff --git a/src/experiments/reducing-points-experiment.py b/src/experiments/reducing-points-experiment.py
new file mode 100644
index 0000000..f0dfe05
--- /dev/null
+++ b/src/experiments/reducing-points-experiment.py
@@ -0,0 +1,64 @@
+import pathlib
+import time
+import torch
+import gpytorch
+from scgp.utils import save_plot_scgp, scgp_fit, save_plot_gp, gp_fit
+
+PATH = pathlib.Path(__file__).parent.parent.parent.absolute()
+DATA_PATH = PATH / "data"
+LOGGING = False
+
+if __name__ == "__main__":
+    datasets = {
+        "uniform_new_HC": DATA_PATH / "Gaussian_logCA0_uniform_J=20_HC.csv",
+        "uniform_new_MC": DATA_PATH / "Gaussian_logCA0_uniform_J=20_MC.csv",
+        "adaptive_new_HC": DATA_PATH / "Gaussian_logCA0_adaptive_J=20_HC.csv",
+        "adaptive_new_MC": DATA_PATH / "Gaussian_logCA0_adaptive_J=20_MC.csv",
+    }
+
+    models = {
+        # "SCGP": {
+        #     "kernel": gpytorch.kernels.RBFKernelGrad,
+        #     "plot": save_plot_scgp,
+        #     "fit": scgp_fit,
+        # },
+        "GP": {
+            "kernel": gpytorch.kernels.RBFKernel,
+            "plot": save_plot_gp,
+            "fit": gp_fit,
+        },
+    }
+    
+    scenarios = {
+        "nobs": list(range(6, 21, 2)),
+    }
+        
+    for model_name, model in models.items():
+        for scenario in scenarios["nobs"]:
+            for dataset_name, dataset_path in datasets.items():
+                start_time = time.time()
+                try:
+                    kernel = model["kernel"]()
+                    train_x, train_y, data, data_likelihood = model["fit"](
+                        dataset_path, 2000, kernel=kernel, nobs=scenario
+                    )
+                    name = f"{model_name}_{scenario}_nobs"
+                    model["plot"](
+                        train_x,
+                        train_y,
+                        data,
+                        data_likelihood,
+                        name,
+                        dataset_name,
+                    )
+                    final_time = time.time() - start_time
+                    print(
+                        f"Finished {model_name} on {dataset_name}"
+                        f" with nobs={scenario}"
+                        f", it took {final_time:.2f}s"
+                    )
+                    del train_x, train_y, data, data_likelihood, kernel
+                    
+                except Exception as e:
+                    print(f"Error on {model_name} on {dataset_name} | {e}")
+                    continue
\ No newline at end of file