Notebook/Colab API + clean estimator __init__ params

examples/01_minimal/config.yml

@@ -76,25 +76,21 @@ graph:
 
     estimator:                          # Posterior estimator network
       _target_: falcon.estimators.Flow   # Flow-based posterior estimation
-      loop:                             # Training loop parameters
-        max_epochs: 300
-        batch_size: 128
-        early_stop_patience: 32         # Early stopping patience
-      network:                          # Neural network architecture
-        net_type: nsf                   # Neural spline flow (alternatives: zuko_gf, maf, naf, etc.)
-        theta_norm: true                # Normalize parameter space
-        norm_momentum: 0.003            # Momentum for online normalization updates
+      max_epochs: 300
+      net_type: nsf                     # Neural spline flow (alternatives: zuko_gf, maf, naf, etc.)
+      lr: 0.01
+      gamma: 0.5                        # Mixing coefficient for amortization weighting
       embedding:                        # Neural embedding for observation x
         _target_: model.E
         _input_: [x]
-      optimizer:                        # Optimizer parameters
-        lr: 0.01
-        lr_decay_factor: 0.5            # LR decay multiplier
-        scheduler_patience: 16          # LR decay after N stagnant epochs
-      inference:                        # Inference and sampling parameters
-        gamma: 0.5                      # Mixing coefficient for amortization weighting
-        discard_samples: false
-        log_ratio_threshold: -20        # Stability cutoff for log ratios
+      batch_size: 128
+      early_stop_patience: 32
+      theta_norm: true                  # Normalize parameter space
+      norm_momentum: 0.003              # Momentum for online normalization updates
+      lr_decay_factor: 0.5              # LR decay multiplier
+      lr_patience: 16                   # LR decay after N stagnant epochs
+      discard_samples: false
+      log_ratio_threshold: -20          # Stability cutoff for log ratios
 
     ray:
       num_gpus: 0                       # GPU count per Ray worker (0 = CPU)