diff --git a/src/cryo_sbi/inference/models/embedding_nets.py b/src/cryo_sbi/inference/models/embedding_nets.py
index e502ff2..c7d0552 100644
--- a/src/cryo_sbi/inference/models/embedding_nets.py
+++ b/src/cryo_sbi/inference/models/embedding_nets.py
@@ -58,6 +58,36 @@ def forward(self, x):
         return x
 
 
+@add_embedding("CRYODRGN_ENCODER")
+class CryoDrgn_Encoder(nn.Module):
+    def __init__(self, output_dimension: int):
+        super(CryoDrgn_Encoder, self).__init__()
+        self.mlp = nn.Sequential(
+            nn.Linear(12892, 1024),
+            nn.GELU(),
+            nn.Linear(1024, 512),
+            nn.GELU(),
+            nn.Linear(512, 512),
+            nn.GELU(),
+            nn.Linear(512, 512),
+            nn.GELU(),
+            nn.Linear(512, 512),
+            nn.GELU(),
+            nn.Linear(512, output_dimension),
+            nn.GELU(),
+        )
+        self.mask = Mask(128, 64, inside=True).mask.flatten()
+        print("Using DRGN Encoder")
+
+    def forward(self, x):
+        if x.dim == 2:
+            x = x.unsqueeze(0)
+        x = torch.fft.fftshift(torch.fft.fft2(x, dim=(-2, -1))).real
+        x = x.flatten(start_dim=1)[:, self.mask]
+        x = self.mlp(x)
+        return x
+
+
 @add_embedding("RESNET18")
 class ResNet18_Encoder(nn.Module):
     def __init__(self, output_dimension: int):