diff --git a/experiments/compuational_comparison.py b/experiments/compuational_comparison.py
index e0dbd86..820dfbd 100644
--- a/experiments/compuational_comparison.py
+++ b/experiments/compuational_comparison.py
@@ -37,7 +37,7 @@
                                          mean_nn_layers=NN_LAYERS, svi_batch_size=5,
                                          kernel_nn_layers=NN_LAYERS, cov_type='diag', normalize_data=True)
 
-    from meta_learn.GPR_meta_pac import GPRegressionMetaLearnedPAC
+    from meta_learn.GPR_meta_mlap import GPRegressionMetaLearnedPAC
 
     model_mlap = GPRegressionMetaLearnedPAC(meta_train_data, num_iter_fit=1000,
                                           svi_batch_size=5, covar_module='NN', mean_module='NN', mean_nn_layers=NN_LAYERS,
diff --git a/experiments/hyperparam_search/launch_hyperparam_sweeps.py b/experiments/hyperparam_search/launch_hyperparam_sweeps.py
index 48ddeec..5964a15 100644
--- a/experiments/hyperparam_search/launch_hyperparam_sweeps.py
+++ b/experiments/hyperparam_search/launch_hyperparam_sweeps.py
@@ -10,7 +10,7 @@
 
 import experiments.hyperparam_search.meta_svgd_hyperparam as meta_svgd_hparam
 import experiments.hyperparam_search.meta_vi_hyperparam as meta_vi_hparam
-import experiments.hyperparam_search.meta_pac_hyperparam as meta_pac_hyperparam
+import experiments.hyperparam_search.meta_mlap_hyperparam as meta_pac_hyperparam
 
 from absl import flags
 from absl import app
diff --git a/experiments/hyperparam_search/meta_pac_hyperparam.py b/experiments/hyperparam_search/meta_mlap_hyperparam.py
similarity index 98%
rename from experiments/hyperparam_search/meta_pac_hyperparam.py
rename to experiments/hyperparam_search/meta_mlap_hyperparam.py
index 9dbb5de..7e7f0da 100644
--- a/experiments/hyperparam_search/meta_pac_hyperparam.py
+++ b/experiments/hyperparam_search/meta_mlap_hyperparam.py
@@ -40,7 +40,7 @@ def train_reg(config, reporter):
         data_train, data_valid, _ = provide_data(dataset=args.dataset, seed=SEED)
 
         # 2) setup model
-        from meta_learn.GPR_meta_pac import GPRegressionMetaLearnedPAC
+        from meta_learn.GPR_meta_mlap import GPRegressionMetaLearnedPAC
         torch.set_num_threads(N_THREADS_PER_RUN)
 
         model = GPRegressionMetaLearnedPAC(data_train, **config)
@@ -74,7 +74,7 @@ def train_test(config):
             data_train, _, data_test = provide_data(dataset=args.dataset, seed=SEED)
 
             # 2) Fit model
-            from meta_learn.GPR_meta_pac import GPRegressionMetaLearnedPAC
+            from meta_learn.GPR_meta_mlap import GPRegressionMetaLearnedPAC
             torch.set_num_threads(N_THREADS_PER_RUN)
             with gpytorch.settings.max_cg_iterations(500):
                 model = GPRegressionMetaLearnedPAC(data_train, **config)
diff --git a/meta_learn/GPR_meta_pac.py b/meta_learn/GPR_meta_mlap.py
similarity index 100%
rename from meta_learn/GPR_meta_pac.py
rename to meta_learn/GPR_meta_mlap.py