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This week in Artificial Intelligence & Security - #37 of 2016
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<abbr class="published" title="2016-09-17T00:00:00">
Sat 17 September 2016 </abbr>
<span class="label"> Category</span>
<a href="./category/ai-ml-security.html"><i class="icon-folder-open"></i>AI & ML, Security</a>
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<p><img alt="cyber" height="300px" src="./cyberpunk/10.jpg" width="400px" /></p>
<h2>Papers</h2>
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<li><a href="https://drive.google.com/file/d/0B3cxcnOkPx9AeWpLVXhkTDJINDQ/view">WaveNet: A Generative Model for Raw Audio</a>.</li>
<li><a href="http://arxiv.org/pdf/1609.02993v1.pdf">Episodic Exploration for Deep Deterministic Policies:
An Application to StarCraft Micromanagement Tasks</a>.</li>
<li><a href="http://arxiv.org/abs/1609.00408">Defeating Image Obfuscation with Deep Learning</a>.</li>
<li><a href="http://arxiv.org/abs/1609.04802">Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network</a>.</li>
</ul>
<h2>News</h2>
<ul>
<li><a href="https://deepmind.com/blog/wavenet-generative-model-raw-audio/">WaveNet: A Generative Model for Raw Audio</a>.</li>
<li><a href="http://distill.pub/2016/augmented-rnns/">Attention and Augmented Recurrent Neural Networks</a>.</li>
<li><a href="http://www.janexwang.com/blog/2016/9/10/attractor-state-part-1">Attractor State, Part 1</a>.</li>
<li><a href="http://www.nextplatform.com/2016/09/13/nvidia-pushes-deep-learning-inference-new-pascal-gpus/">NVIDIA Announces Tesla P40 & Tesla P4 - Neural Network Inference, Big & Small</a>.</li>
<li><a href="http://www.nextplatform.com/2016/09/07/next-wave-deep-learning-architectures/">The Next Wave of Deep Learning Architectures</a>.</li>
<li><a href="https://medium.com/@katecrawford/artificial-intelligence-is-hard-to-see-a71e74f386db#.icgq55dzd">Artificial intelligence is hard to see</a>.</li>
<li><a href="https://www.technologyreview.com/s/602344/the-extraordinary-link-between-deep-neural-networks-and-the-nature-of-the-universe/">The Extraordinary Link Between Deep Neural Networks and the Nature of the Universe</a>.</li>
<li><a href="http://aiimpacts.org/what-if-you-turned-the-worlds-hardware-into-ai-minds/">What if you turned the world’s hardware into AI minds?</a>.</li>
<li><a href="https://www.technologyreview.com/s/602274/three-grand-challenges-for-brain-science-that-can-be-solved-in-10-years/">Three Grand Challenges for Brain Science That Can Be Solved in 10 Years</a>.</li>
</ul>
<h2>Videos</h2>
<ul>
<li><a href="https://www.youtube.com/watch?v=Xogn6veSyxA">Ian Goodfellow's lecture about Batch Normalization and Convolutional Networks.</a></li>
<li><a href="https://www.youtube.com/watch?v=x1kf4Zojtb0">Nando de Freita's Learning to learn and compositionality with deep recurrent neural networks</a>.</li>
<li><a href="https://www.youtube.com/watch?v=9c4z6YsBGQ0&feature=youtu.be">Generative Visual Manipulation on the Natural Image Manifold</a>.</li>
<li><a href="http://cmusatyalab.github.io/openface/demo-4-sphere/">CMU's Real-Time Face Embedding Visualization</a>.</li>
</ul>
<h2>Tools</h2>
<ul>
<li><a href="https://github.com/yaringal/DropoutUncertaintyExps#updated-results-compared-to-the-original-paper">Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"</a>.</li>
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