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194	194	=== 2. Full VBI Inference workflow ===
195	195
196		-Contains all VBI components required to run an inference workflow, from __prior sampling__ and __simulation__ to __posterior training__ and __posterior sampling__.
	196	+Contains all VBI components required to run an inference workflow (e.g., inference configuration, model, simulator, train posterior, sample posterior).
197	197
198		-The workflow starts with **ConfigInference**, which builds the configuration inputs needed by the workflow. It samples parameter values from the prior distribution to generate __theta__ and prepares the feature-extraction configuration (__cfg__) used later in the pipeline.
199		-
200		-Next, **SimulationRunner** executes the selected **VBI model** for a batch of parameter samples (theta) using the chosen backend (//cpp//, //cupy// or //numba//). It selects the requested output signal from the model result and extracts the summary features defined in cfg, producing the __feature matrix__ used for training.
201		-
202		-The resulting features and parameter samples are then passed to **TrainPosterior**, which standardizes the feature matrix with //StandardScaler //and trains a posterior distribution using an SBI method (//SNPE//, //SNLE//, or //SNRE//). In the last step, **SamplePosterior** draws parameter samples from the trained posterior distribution, conditioned on the selected observed feature vector.
203		-
204	204	[[image:vbi_workflow.png||height="590" width="1100"]]
205	205
206	206	=== 3. Configuring model parameters using the PhasePlaneWidget: ===