Adversarial

Interaction-aware Multi-agent Tracking and Probabilistic Behavior Prediction via Adversarial Learning. (arXiv:1904.02390v1 [cs.RO])

[ad_1] In order to enable high-quality decision making and motion planning of intelligent systems such as robotics and autonomous vehicles, accurate probabilistic predictions for surrounding interactive objects is a crucial...

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Generative Adversarial Networks for text using word2vec intermediaries. (arXiv:1904.02293v1 [cs.CL])

[ad_1] Generative adversarial networks (GANs) have shown considerable success, especially in the realistic generation of images. In this work, we apply similar techniques for the generation of text. We propose...

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Bridging Adversarial Robustness and Gradient Interpretability. (arXiv:1903.11626v1 [cs.LG])

[ad_1] Adversarial training is a training scheme designed to counter adversarial attacks by augmenting the training dataset with adversarial examples. Surprisingly, several studies have observed that loss gradients from adversarially...

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Humans can predict how machines (mis)classify adversarial images – VentureBeat

[ad_1] Humans can predict how machines (mis)classify adversarial images  VentureBeatWe question how AI could label an image of a dog as a pineapple. But research shows there's a logic to these...

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DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC.

[ad_1] Related Articles DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC. PLoS One. 2019;14(3):e0212849 Authors: Theagarajan R, Bhanu B Abstract Human embryonic stem cells (hESC),...

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Active Perception in Adversarial Scenarios using Maximum Entropy Deep Reinforcement Learning. (arXiv:1902.05644v1 [cs.AI])

[ad_1] We pose an active perception problem where an autonomous agent actively interacts with a second agent with potentially adversarial behaviors. Given the uncertainty in the intent of the other...

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Robustness of Generalized Learning Vector Quantization Models against Adversarial Attacks. (arXiv:1902.00577v1 [cs.LG])

[ad_1] Adversarial attacks and the development of (deep) neural networks robust against them are currently two widely researched topics. The robustness of Learning Vector Quantization (LVQ) models against adversarial attacks...

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An automatic diagnostic network using skew-robust adversarial discriminative domain adaptation to evaluate the severity of depression.

[ad_1] Related Articles An automatic diagnostic network using skew-robust adversarial discriminative domain adaptation to evaluate the severity of depression. Comput Methods Programs Biomed. 2019 Jan 17;: Authors: Sun B, Zhang...

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Generative Adversarial Classifier for Handwriting Characters Super-Resolution. (arXiv:1901.06199v1 [cs.CV])

[ad_1] Generative Adversarial Networks (GAN) receive great attentions recently due to its excellent performance in image generation, transformation, and super-resolution. However, GAN has rarely been studied and trained for classification,...

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Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning based Registration.

[ad_1] Related Articles Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning based Registration. Med Image Comput Comput Assist Interv. 2018 Sep;11070:739-746 Authors: Fan J, Cao X, Xue Z,...

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[Applications of generative adversarial networks in medical image processing].

[ad_1] Related Articles [Applications of generative adversarial networks in medical image processing]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2018 Jun 01;35(6):970-976 Authors: Pan D, Jia L, Zeng...

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SUSAN: segment unannotated image structure using adversarial network.

[ad_1] Related Articles SUSAN: segment unannotated image structure using adversarial network. Magn Reson Med. 2018 Dec 10;: Authors: Liu F Abstract PURPOSE: To describe and evaluate a segmentation method using...

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Adversarial deformation regularization for training image registration neural networks

[ad_1] Hu, Y; Gibson, E; Ghavami, N; Bonmati, E; Moore, CM; Emberton, M; Vercauteren, T; ... Barratt, DC; + view all Hu, Y; Gibson, E; Ghavami, N; Bonmati, E; Moore,...

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Generating Text via Adversarial Training

[ad_1] There was a really cute paper at the GAN workshop this year, Generating Text via Adversarial Training by Zhang, Gan, and Carin. In particular, they make a couple of...

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Adversarial validation, part two

Adversarial validation, part two Source link

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Generative Adversarial Networks and the Rise of Fake Faces: an Intellectual Property Perspective

The tremendous growth in the artificial intelligence (AI) sector over the last several years may be attributed in large part to the proliferation of so-called big data.  But even today,...

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Semi-supervised Learning on Graphs with Generative Adversarial Nets. (arXiv:1809.00130v1 [cs.SI])

We investigate how generative adversarial nets (GANs) can help semi-supervised learning on graphs. We first provide insights on working principles of adversarial learning over graphs and then present GraphSGAN, a...

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Fooling Image Recognition with Adversarial Examples

Fooling Image Recognition with Adversarial Examples Source link

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Multi-Agent Generative Adversarial Imitation Learning. (arXiv:1807.09936v1 [cs.LG])

Imitation learning algorithms can be used to learn a policy from expert demonstrations without access to a reward signal. However, most existing approaches are not applicable in multi-agent settings due...

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