GitHub - kevinroy007/NLVAR_subgradient_descent: Non-linear topology identification using Deep Learning. Sparsity (lasso) is enforced in the sensor connections. The non-convex and non-differentiable function is solved using sub-gradient descent algorithm.

This repository contains two different model formulations for evaluating linear and nonlinear VAR models:

Formulation A linear_validation.py: Executes the linear VAR (Vector Autoregression) model using a predefined set of hyperparameters.

nonlinear_validation.py: Runs the nonlinear VAR (NLVAR) model with the desired configuration.

python linearvalidation.py or

python nonlinearvalidation.py depending on the model you wish to evaluate.

Formulation B Implements the VAR model under Formulation B.

Navigate to the FormulationB/ folder and run:

python var_lip.py

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
GitHub		GitHub
code_compare		code_compare
lundin		lundin
results		results
.DS_Store		.DS_Store
.gitignore		.gitignore
LICENSE		LICENSE
LinearVAR.py		LinearVAR.py
LinearVAR_Kevin.py		LinearVAR_Kevin.py
NonlinearVAR.py		NonlinearVAR.py
NonlinearVAR_old.py		NonlinearVAR_old.py
README.md		README.md
compute_gradients_Compare.py		compute_gradients_Compare.py
compute_gradients_Linear.py		compute_gradients_Linear.py
exp_learn.py		exp_learn.py
graph.py		graph.py
learn_model.py		learn_model.py
nlTools.py		nlTools.py
nlv_hat_0		nlv_hat_0
nlv_true_0		nlv_true_0
projection_simplex.py		projection_simplex.py
resultcheck.py		resultcheck.py
show_some_results.py		show_some_results.py
test_arithmetic_act.py		test_arithmetic_act.py
test_learn.py		test_learn.py
test_nnl.py		test_nnl.py
update_params.py		update_params.py
utils_exp.py		utils_exp.py
var.py		var.py

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