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Beat Buesser
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Update notebooks
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35 files changed

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‎notebooks/adaptive_defence_evaluations/evaluation_12_EMPIR.ipynb

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"import numpy as np\n",
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"\n",
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"from art.estimators.classification import TensorFlowClassifier\n",
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"from art.attacks import ProjectedGradientDescent"
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"from art.attacks.evasion import ProjectedGradientDescent"
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.10"
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"version": "3.7.7"
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}
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},
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"nbformat": 4,

‎notebooks/adversarial_patch/attack_adversarial_patch.ipynb

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"from tensorflow.keras.preprocessing import image\n",
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"\n",
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"from art.estimators.classification import TensorFlowClassifier\n",
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"from art.attacks import AdversarialPatch"
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"from art.attacks.evasion import AdversarialPatch"
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]
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},
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{
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv36_TF1_14_keras225",
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"display_name": "Python 3",
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"language": "python",
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"name": "venv36_tf1_14_keras225"
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.8"
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"version": "3.7.7"
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}
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},
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"nbformat": 4,

‎notebooks/adversarial_patch/attack_adversarial_patch_TensorFlowV2.ipynb

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"from tensorflow.keras.preprocessing import image\n",
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"\n",
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"from art.estimators.classification import TensorFlowV2Classifier, EnsembleClassifier\n",
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"from art.attacks import AdversarialPatch"
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"from art.attacks.evasion import AdversarialPatch"
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]
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},
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{
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv36_TF210_keras231",
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"display_name": "Python 3",
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"language": "python",
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"name": "venv36_tf210_keras231"
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.8"
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"version": "3.7.7"
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}
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"nbformat": 4,

‎notebooks/adversarial_retraining.ipynb

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"\n",
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"from art.config import ART_DATA_PATH\n",
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"from art.estimators.classification import KerasClassifier\n",
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"from art.attacks import ProjectedGradientDescent\n",
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"from art.attacks.evasion import ProjectedGradientDescent\n",
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"from art.utils import get_file"
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]
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},
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Downloading data from https://s3.amazonaws.com/img-datasets/mnist.npz\n",
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"11493376/11490434 [==============================] - 0s 0us/step\n"
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]
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}
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],
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"source": [
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"(X_train, y_train), (X_test, y_test) = mnist.load_data()\n",
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"X_train = X_train.reshape(X_train.shape[0], 28, 28, 1).astype('float32') / 255\n",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Accuracy on first 10 adversarial test samples: 1.000000\n"
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"Accuracy on first 10 adversarial test samples: 0.900000\n"
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]
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}
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],
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Accuracy on first 100 adversarial test samples: 0.450000\n"
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"Accuracy on first 100 adversarial test samples: 0.470000\n"
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]
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}
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],
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv36",
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.8"
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"version": "3.7.7"
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}
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},
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"nbformat": 4,

‎notebooks/adversarial_training_mnist.ipynb

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‎notebooks/art-for-tensorflow-v2-callable.ipynb

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‎notebooks/art-for-tensorflow-v2-keras.ipynb

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‎notebooks/attack_decision_based_boundary.ipynb

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‎notebooks/attack_decision_tree.ipynb

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‎notebooks/attack_defence_imagenet.ipynb

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‎notebooks/attack_hopskipjump.ipynb

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‎notebooks/classifier_blackbox.ipynb

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"\n",
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"from art.config import ART_DATA_PATH\n",
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"from art.estimators.classification import BlackBoxClassifier\n",
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"from art.attacks import HopSkipJump\n",
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"from art.attacks.evasion import HopSkipJump\n",
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"from art.utils import to_categorical\n",
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"from art.utils import load_dataset, get_file, compute_accuracy"
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]
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.1"
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"version": "3.7.7"
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}
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"nbformat": 4,

‎notebooks/classifier_blackbox_tesseract.ipynb

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"\n",
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"from art.config import ART_DATA_PATH\n",
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"from art.estimators.classification import BlackBoxClassifier\n",
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"from art.defences import JpegCompression\n",
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"from art.attacks import HopSkipJump\n",
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"from art.attacks import ZooAttack\n",
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"from art.defences.preprocessor import JpegCompression\n",
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"from art.attacks.evasion import HopSkipJump\n",
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"from art.attacks.evasion import ZooAttack\n",
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"from art.utils import to_categorical\n",
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"from art.utils import load_dataset, get_file, compute_accuracy"
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]
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.10"
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"version": "3.7.7"
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}
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},
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"nbformat": 4,

‎notebooks/classifier_catboost.ipynb

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‎notebooks/classifier_gpy_gaussian_process.ipynb

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‎notebooks/classifier_lightgbm.ipynb

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‎notebooks/classifier_scikitlearn_AdaBoostClassifier.ipynb

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‎notebooks/classifier_scikitlearn_BaggingClassifier.ipynb

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‎notebooks/classifier_scikitlearn_DecisionTreeClassifier.ipynb

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‎notebooks/classifier_scikitlearn_ExtraTreesClassifier.ipynb

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‎notebooks/classifier_scikitlearn_GradientBoostingClassifier.ipynb

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‎notebooks/classifier_scikitlearn_LogisticRegression.ipynb

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‎notebooks/classifier_scikitlearn_RandomForestClassifier.ipynb

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‎notebooks/classifier_scikitlearn_SVC_LinearSVC.ipynb

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‎notebooks/classifier_scikitlearn_pipeline_pca_cv_svc.ipynb

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‎notebooks/classifier_xgboost.ipynb

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‎notebooks/detection_adversarial_samples_cifar10.ipynb

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‎notebooks/fabric_for_deep_learning_adversarial_samples_fashion_mnist.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.4.10"
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"version": "3.7.7"
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"nbformat": 4,

‎notebooks/model_inversion_attacks_mnist.ipynb

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"from numpy.random import seed\n",
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"seed(123)\n",
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"\n",
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"from art.classifiers import KerasClassifier\n",
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"from art.attacks import MIFace\n",
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"from art.estimators.classification import KerasClassifier\n",
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"from art.attacks.inference import MIFace\n",
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"from art.utils import load_dataset\n",
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"\n",
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"%matplotlib inline\n",
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"name": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.7"
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"nbformat": 4,

‎notebooks/output_randomized_smoothing_mnist.ipynb

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"version": "0.3.2"
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},
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"kernelspec": {
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"display_name": "venv36_TF210_keras231",
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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"language_info": {
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"name": "python",
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"version": "3.7.7"
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‎notebooks/poisoning_attack_feature_collision.ipynb

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"\n",
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"from art.config import ART_DATA_PATH\n",
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"from art.utils import load_dataset, get_file\n",
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"from art.classifiers import KerasClassifier\n",
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"from art.estimators.classification import KerasClassifier\n",
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"from art.attacks.poisoning import FeatureCollisionAttack\n",
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"\n",
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"import numpy as np\n",
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"name": "python",
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‎notebooks/poisoning_attack_svm.ipynb

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‎notebooks/poisoning_dataset_mnist.ipynb

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‎notebooks/provenance_defence.ipynb

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‎notebooks/robustness_verification_clique_method_tree_ensembles_gradient_boosted_decision_trees_classifiers.ipynb

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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language_info": {
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"version": "3.7.7"
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}
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},
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"nbformat": 4,

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