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diff --git a/studies/broad_comparison_1d.py b/studies/broad_comparison_1d.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c55c8f213d7178857aadc144eeb5614f23264b9
--- /dev/null
+++ b/studies/broad_comparison_1d.py
@@ -0,0 +1,31 @@
+"""
+Produces the 1D results of the broad comparison across architectures and
+dynamics.
+
+Full prediction learning with one-step supervised training.
+"""
+CONFIGS = [
+    {
+        "scenario": scene,
+        "task": "predict",
+        "net": net,
+        "train": "one",
+        "start_seed": s,
+        "num_seeds": 10,
+    }
+    for s in [0, 10, 20, 30, 40]
+    for net in [
+        "Conv;34;10;relu",  # 31'757 params, 11 receptive field per direction
+        "UNet;12;2;relu",  # 27'193 params, 29 receptive field per direction
+        "Res;26;8;relu",  # 32'943 params, 16 receptive field per direction
+        "FNO;12;18;4;gelu",  # 32'527 params, inf receptive field per direction
+        "Dil;2;32;2;relu",  # 31'777 params, 20 receptive field per direction
+    ]
+    for scene in [
+        "diff_disp",
+        "diff_burgers",
+        "diff_kdv",
+        "diff_ks_cons",  # was not used in the paper in the end
+        "diff_ks",
+    ]
+]
diff --git a/studies/broad_comparison_2d.py b/studies/broad_comparison_2d.py
new file mode 100644
index 0000000000000000000000000000000000000000..bb9ea443996b95005869cff4b9277235430085da
--- /dev/null
+++ b/studies/broad_comparison_2d.py
@@ -0,0 +1,32 @@
+"""
+Produces the 2D results of the broad comparison across architectures and
+dynamics.
+
+Full prediction learning with one-step supervised training.
+"""
+CONFIGS = [
+    {
+        "scenario": scene,
+        "task": "predict",
+        "net": net,
+        "train": "one",
+        "start_seed": s,
+        "num_seeds": 1,
+        "num_spatial_dims": 2,
+    }
+    for s in range(20)
+    for net in [
+        "Conv;26;11;relu",  # 61'595 params, 12 receptive field per direction
+        "UNet;10;2;relu",  # 55'661 params, 29 receptive field per direction
+        "Res;26;5;relu",  # 61'179 params, 10 receptive field per direction
+        "FNO;10;6;4;gelu",  # 57'787 params, inf receptive field per direction
+        "Dil;2;26;2;relu",  # 61'699 params, 20 receptive field per direction
+    ]
+    for scene in [
+        "phy_aniso_diff",
+        "diff_burgers",  # Uses the two-channel version in 2D
+        "diff_ks",
+        "phy_kolm_flow",
+        "phy_gs_type",
+    ]
+]
diff --git a/studies/broad_comparison_3d.py b/studies/broad_comparison_3d.py
new file mode 100644
index 0000000000000000000000000000000000000000..035c1af3c4a1e6e831ff8db95216b02dbb839057
--- /dev/null
+++ b/studies/broad_comparison_3d.py
@@ -0,0 +1,34 @@
+"""
+Produces the 3D results of the broad comparison across architectures and
+dynamics.
+
+Full prediction learning with one-step supervised training.
+"""
+CONFIGS = [
+    {
+        "scenario": scene,
+        "task": "predict",
+        "net": net,
+        "train": "one",
+        "start_seed": s,
+        "num_seeds": 1,
+        "num_spatial_dims": 3,
+        "num_points": 32,
+        "num_test_samples": 10,
+    }
+    for s in range(20)
+    for net in [
+        "Conv;26;12;relu",  # 202'489 params, 13 receptive field per direction
+        "UNet;11;2;relu",  # 200'322 params, 29 receptive field per direction
+        "Res;25;6;relu",  # 202'876 params, 12 receptive field per direction
+        "FNO;5;7;4;gelu",  # 196'246 params, inf receptive field
+        "Dil;2;27;2;relu",  # 197'722 params, 20 receptive field per direction
+    ]
+    for scene in [
+        "phy_unbal_adv",
+        "diff_burgers",  # Uses the three-channel version in 3D
+        "diff_ks",
+        "phy_gs",
+        "phy_sh",
+    ]
+]
diff --git a/studies/ks_2d_reduced_res.py b/studies/ks_2d_reduced_res.py
new file mode 100644
index 0000000000000000000000000000000000000000..af1888960532382000f4265f5abd650a96b0f51e
--- /dev/null
+++ b/studies/ks_2d_reduced_res.py
@@ -0,0 +1,25 @@
+"""
+Produces the result for underresolved Kuramoto-Sivashinsky in 2D.
+
+Full prediction learning with one-step supervised training.
+"""
+CONFIGS = [
+    {
+        "scenario": "diff_ks",
+        "task": "predict",
+        "net": net,
+        "train": "one",
+        "start_seed": s,
+        "num_seeds": 10,
+        "num_spatial_dims": 2,
+        "num_points": 32,
+    }
+    for s in [0, 10]
+    for net in [
+        "Conv;26;11;relu",  # 61'595 params, 12 receptive field per direction
+        "UNet;10;2;relu",  # 55'661 params, 29 receptive field per direction
+        "Res;26;5;relu",  # 61'179 params, 10 receptive field per direction
+        "FNO;10;6;4;gelu",  # 57'787 params, inf receptive field per direction
+        "Dil;2;26;2;relu",  # 61'699 params, 20 receptive field per direction
+    ]
+]