March 2, 2021
Generative Models
We visually inspect the images generated by GAN. But, with a twist.
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We visually inspect the images generated by GAN. But, with a twist.
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Build CIFAR10 classifier(s) using different deep learning frameworks and hardware accelerators
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Counting item of interest in an image or a video is an interesting problem. Too few and you can use YOLO or SSD based object detection models, too many and you can use...
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We use soft attention based technique to improve vanilla image caption model that we saw in the previous post.
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Generating image caption using Convolutional and Recurrent Neural Networks
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The mixture density network can represent general conditional probability densities using a set of learned mixture models.
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In this post, we train two agents to play tennis against each other
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We use deep deterministic policy gradients to solve unity ml-agent with continuous action space
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We use simple policy based methods to solve CartPole environment and compare their performance
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In this post, I compare the time taken to train a Convolutional neural network on native 1080ti and the accelerators available on Google Colaboratory
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It can provide many useful applications but at what cost ? Privacy, mass surveillance..
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Can neural networks learn to write stories ? Can they be taught to crack jokes or write articles ?
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What do filters in a convolutional neural network learn? How do we visualize a convolutional layer ? Can the Neural networks dream and if they do, do they dream of electric sheep ?
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The paper presents a technique to perform one shot learning with one or few examples per dataset.
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Can computers learn to draw like Picasso, Vangogh, Monet or any other artist ? Gatys et al. introduce an algorithm that uses a Deep neural network to generate artistic images of high perceptual quality.
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Imagine being able to learn the probability distribution of your dataset and sample from the learned distribution.
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