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adversarial training

355 papers with code · Adversarial

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Greatest papers with code

Ensemble Adversarial Training: Attacks and Defenses

ICLR 2018 tensorflow/models

We show that this form of adversarial training converges to a degenerate global minimum, wherein small curvature artifacts near the data points obfuscate a linear approximation of the loss.

ADVERSARIAL TRAINING

Adversarial Machine Learning at Scale

4 Nov 2016tensorflow/models

Adversarial examples are malicious inputs designed to fool machine learning models.

ADVERSARIAL TRAINING

Adversarial Training Methods for Semi-Supervised Text Classification

25 May 2016tensorflow/models

Adversarial training provides a means of regularizing supervised learning algorithms while virtual adversarial training is able to extend supervised learning algorithms to the semi-supervised setting.

ADVERSARIAL TRAINING SENTIMENT ANALYSIS TEXT CLASSIFICATION WORD EMBEDDINGS

Adversarial Logit Pairing

NeurIPS 2018 tensorflow/models

In this paper, we develop improved techniques for defending against adversarial examples at scale.

ADVERSARIAL TRAINING

Learning from Simulated and Unsupervised Images through Adversarial Training

CVPR 2017 tensorflow/models

With recent progress in graphics, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations.

ADVERSARIAL TRAINING DOMAIN ADAPTATION GAZE ESTIMATION HAND POSE ESTIMATION IMAGE-TO-IMAGE TRANSLATION

YOLOv4: Optimal Speed and Accuracy of Object Detection

23 Apr 2020pjreddie/darknet

There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy.

ADVERSARIAL TRAINING DATA AUGMENTATION REAL-TIME OBJECT DETECTION

Adversarial Examples Improve Image Recognition

CVPR 2020 rwightman/pytorch-image-models

We show that AdvProp improves a wide range of models on various image recognition tasks and performs better when the models are bigger.

ADVERSARIAL TRAINING IMAGE CLASSIFICATION

Explaining and Harnessing Adversarial Examples

20 Dec 2014tensorflow/cleverhans

Several machine learning models, including neural networks, consistently misclassify adversarial examples---inputs formed by applying small but intentionally worst-case perturbations to examples from the dataset, such that the perturbed input results in the model outputting an incorrect answer with high confidence.

ADVERSARIAL TRAINING IMAGE CLASSIFICATION

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

23 Nov 2018thunil/TecoGAN

Additionally, we propose a first set of metrics to quantitatively evaluate the accuracy as well as the perceptual quality of the temporal evolution.

ADVERSARIAL TRAINING IMAGE SUPER-RESOLUTION MOTION COMPENSATION SUPER RESOLUTION VIDEO GENERATION VIDEO SUPER-RESOLUTION

Are Labels Required for Improving Adversarial Robustness?

NeurIPS 2019 deepmind/deepmind-research

Recent work has uncovered the interesting (and somewhat surprising) finding that training models to be invariant to adversarial perturbations requires substantially larger datasets than those required for standard classification.

ADVERSARIAL TRAINING