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CodeOcean test runners for FairNNV, ProbVer, ModelStar, VideoStar, and GNNV with environment setup, README documentation, and test coverage matching original NNV 3.0 configurations.
MATLAB R2024b's importNetworkFromONNX creates nnet.onnx.layer.AddLayer variants instead of nnet.cnn.layer.AdditionLayer for ONNX Add operations. This caused test_regression_acasxu_vnnlib to fail with "Unsupported Class of Layer". Add contains(class(L), 'AddLayer') check and use direct constructor to handle both standard and ONNX-imported addition layers.
- Add generate_figures.py for publication figures and LaTeX tables - Generate ModelStar, GNNV, FairNNV, VideoStar, ProbVer outputs - Fix ProbVer Direction_trainer to save .mat instead of .npz - Remove pyenv dependency from ProbReach_ImageStar and Prob_reach - Make FairNNV and VideoStar paths portable (auto-detect nnvDir) - Add ProbVer ONNX model, vnnlib properties, and results - Add FairNNV results (counterfactual/individual fairness CSVs)
Restore matlab2nnv.m, Direction_trainer.py, ProbReach_ImageStar.m, and Prob_reach.m to their original versions to fix CI test failures.
The codeocean capsule contains a standalone NNV copy with +nnet package overrides that shadow MATLAB's built-in ONNX layer definitions when genpath adds them to the path. This caused importNetworkFromONNX to generate custom AddLayer classes instead of standard AdditionLayer, breaking test_regression_acasxu_vnnlib and test_matlab2nnv. Also update ModelStar figure to prevent timing labels from intersecting the upper axis boundary.
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Add NNV 3.0 submission folder with instructions on reproducing artifacts.