diff --git a/setup.cfg b/setup.cfg
index 24c79d02..7be378de 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -39,7 +39,7 @@ install_requires =
     numpy>=1.20
     lifelines>=0.27
     opacus>=1.3
-    decaf-synthetic-data>=0.1.5
+    decaf-synthetic-data>=0.1.6
     optuna>=3.1
     shap
     tqdm
diff --git a/src/synthcity/metrics/eval_performance.py b/src/synthcity/metrics/eval_performance.py
index fc44cf8d..8a24345e 100644
--- a/src/synthcity/metrics/eval_performance.py
+++ b/src/synthcity/metrics/eval_performance.py
@@ -675,7 +675,7 @@ def evaluate(
                     "n_jobs": 2,
                     "verbosity": 0,
                     "depth": 3,
-                    "strategy": "weibull",  # "weibull", "debiased_bce"
+                    "strategy": "debiased_bce",  # "weibull", "debiased_bce"
                     "random_state": self._random_state,
                 },
                 X_gt,
@@ -705,7 +705,7 @@ def evaluate(
                     "n_jobs": 2,
                     "verbosity": 0,
                     "depth": 3,
-                    "strategy": "weibull",  # "weibull", "debiased_bce"
+                    "strategy": "debiased_bce",  # "weibull", "debiased_bce"
                     "random_state": self._random_state,
                 },
                 X_gt,
@@ -1033,7 +1033,7 @@ def evaluate(
                 n_jobs=2,
                 verbosity=0,
                 depth=3,
-                strategy="weibull",  # "weibull", "debiased_bce"
+                strategy="debiased_bce",  # "weibull", "debiased_bce"
                 random_state=self._random_state,
             )
 
diff --git a/src/synthcity/plugins/core/models/ts_model.py b/src/synthcity/plugins/core/models/ts_model.py
index aa5ef333..a7026146 100644
--- a/src/synthcity/plugins/core/models/ts_model.py
+++ b/src/synthcity/plugins/core/models/ts_model.py
@@ -704,6 +704,7 @@ def __init__(
 
         self.device = device
         self.window_size = window_size
+        self.n_static_units_in = n_static_units_in
         self.model = MLP(
             task_type="regression",
             n_units_in=n_static_units_in + n_temporal_units_in * window_size,
@@ -719,7 +720,7 @@ def __init__(
     def forward(
         self, static_data: torch.Tensor, temporal_data: torch.Tensor
     ) -> torch.Tensor:
-        if len(static_data) != len(temporal_data):
+        if self.n_static_units_in > 0 and len(static_data) != len(temporal_data):
             raise ValueError("Length mismatch between static and temporal data")
 
         batch_size, seq_len, n_feats = temporal_data.shape
diff --git a/src/synthcity/utils/datasets/time_series/pbc.py b/src/synthcity/utils/datasets/time_series/pbc.py
index 57c7026f..185b0477 100644
--- a/src/synthcity/utils/datasets/time_series/pbc.py
+++ b/src/synthcity/utils/datasets/time_series/pbc.py
@@ -62,7 +62,7 @@ def _load_pbc_dataset(self, sequential: bool = True) -> Tuple:
             data = pd.read_csv(df_path)
 
         data["time"] = data["years"] - data["year"]
-        data = data.sort_values(by="time")
+        data = data.sort_values(by=["id", "time"], ignore_index=True)
         data["histologic"] = data["histologic"].astype(str)
         dat_cat = data[
             ["drug", "sex", "ascites", "hepatomegaly", "spiders", "edema", "histologic"]
@@ -136,6 +136,14 @@ def _load_pbc_dataset(self, sequential: bool = True) -> Tuple:
             patient = x_[data["id"] == id_]
 
             patient_static = patient[static_cols]
+            if (
+                not (patient_static.iloc[0] == patient_static).all().all()
+            ):  # pragma: no cover
+                # This is a sanity check.
+                raise RuntimeError(
+                    "Found patient with static data that are not actually fixed:\n"
+                    f"id: {id_}\n{patient_static}"
+                )
             x_static.append(patient_static.values[0].tolist())
 
             patient_temporal = patient[temporal_cols]