diff --git a/src/aihwkit/simulator/tiles/periphery.py b/src/aihwkit/simulator/tiles/periphery.py
index 420ff013..4b17628c 100644
--- a/src/aihwkit/simulator/tiles/periphery.py
+++ b/src/aihwkit/simulator/tiles/periphery.py
@@ -979,6 +979,10 @@ def add_quant_periphery_bias(
         Tensor
             The output of the tile added with the bias
         """
+        # Ensure an iterable tuple for .view(*tensor_view)
+        if tensor_view is None:
+            tensor_view = self.get_tensor_view(output.dim())
+
         if self.bias_quantizer is None:
             return output + self.bias.view(*tensor_view)
 
diff --git a/src/rpucuda/rpu_pulsed_device.h b/src/rpucuda/rpu_pulsed_device.h
index 47a1cc6a..dfcc2707 100644
--- a/src/rpucuda/rpu_pulsed_device.h
+++ b/src/rpucuda/rpu_pulsed_device.h
@@ -110,7 +110,6 @@ template <typename T> struct PulsedRPUDeviceMetaParameter : PulsedRPUDeviceMetaP
     }
     reset_dtod = MAX(reset_dtod, (T)0.0);
     this->reset_std = MAX(this->reset_std, (T)0.0);
-    reset = MAX(reset, (T)0.0);
   };
 };
 
diff --git a/tests/test_specific_tiles.py b/tests/test_specific_tiles.py
index 34eac448..bf18d7f1 100644
--- a/tests/test_specific_tiles.py
+++ b/tests/test_specific_tiles.py
@@ -150,3 +150,67 @@ def test_decay(self):
             self.assertAlmostEqual(bias[0].item(), gamma * (a - b) + c - d, 5)
 
         self.assertAlmostEqual(weight[0][0].item(), gamma * (a - b) + c - d, 5)
+
+    def test_decay_with_negative_reset_bias(self):
+        """Test that decay keeps a negative reset bias."""
+        # pylint: disable=invalid-name, too-many-locals
+
+        lifetime = 100.0
+        gamma = 0.1
+        reset_bias = -0.3
+        rpu_config = self.get_transfer_compound(
+            gamma=gamma, lifetime=lifetime, lifetime_dtod=0.0, reset=reset_bias, reset_std=0.0
+        )
+        model = self.get_layer(in_features=2, out_features=1, rpu_config=rpu_config)
+
+        weight, bias = model.get_weights()
+        model.set_weights(weight * 0.0, bias * 0.0 if bias is not None else None)
+
+        analog_tile = next(model.analog_tiles())
+        params = analog_tile.get_hidden_parameters()
+        shape = params["hidden_weights_0_0"].shape
+
+        a, b, c, d = 0.47, 0.21, 0.64, 0.12
+        params["hidden_weights_0_0"] = a * ones(*shape)
+        params["hidden_weights_1_0"] = b * ones(*shape)
+        params["hidden_weights_0_1"] = c * ones(*shape)
+        params["hidden_weights_1_1"] = d * ones(*shape)
+
+        a_dcy, b_dcy, c_dcy, d_dcy = 0.95, 0.28, 0.33, 0.12
+        params["decay_scales_0_0"] = a_dcy * ones(*shape)
+        params["decay_scales_1_0"] = b_dcy * ones(*shape)
+        params["decay_scales_0_1"] = c_dcy * ones(*shape)
+        params["decay_scales_1_1"] = d_dcy * ones(*shape)
+
+        analog_tile.set_hidden_parameters(params)
+        x_b = Tensor([[0.1, 0.2], [0.2, 0.4]])
+        y_b = Tensor([[0.3], [0.6]])
+
+        if self.use_cuda:
+            x_b = x_b.cuda()
+            y_b = y_b.cuda()
+
+        opt = AnalogSGD(model.parameters(), lr=0.0)
+
+        epochs = 2
+        for _ in range(epochs):
+            opt.zero_grad()
+            pred = model(x_b)
+            loss = mse_loss(pred, y_b)
+
+            loss.backward()
+            opt.step()
+
+        weight, bias = model.get_weights()
+
+        a = (a - reset_bias) * pow(a_dcy, epochs) + reset_bias
+        b = (b - reset_bias) * pow(b_dcy, epochs) + reset_bias
+        c = (c - reset_bias) * pow(c_dcy, epochs) + reset_bias
+        d = (d - reset_bias) * pow(d_dcy, epochs) + reset_bias
+
+        if self.digital_bias:
+            self.assertAlmostEqual(bias[0].item(), 0.0)
+        if self.bias and not self.digital_bias:
+            self.assertAlmostEqual(bias[0].item(), gamma * (a - b) + c - d, 5)
+
+        self.assertAlmostEqual(weight[0][0].item(), gamma * (a - b) + c - d, 5)