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AutoML: A Survey of the State-of-the-Art
Deep learning has penetrated all aspects of our lives and brought us gre...
08/02/2019 ∙ by Xin He, et al. ∙
257
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One Model To Rule Them All
We present a new flavor of Variational Autoencoder (VAE) that interpolat...
08/08/2019 ∙ by Felix Berkhahn, et al. ∙
40
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Deep Generalized Max Pooling
Global pooling layers are an essential part of Convolutional Neural Netw...
08/14/2019 ∙ by Vincent Christlein, et al. ∙
40
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Deep Kernel Learning for Clustering
We propose a deep learning approach for discovering kernels tailored to ...
08/09/2019 ∙ by Chieh Wu, et al. ∙
38
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Bayesian Inference for Large Scale Image Classification
Bayesian inference promises to ground and improve the performance of dee...
08/09/2019 ∙ by Jonathan Heek, et al. ∙
38
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DoorGym: A Scalable Door Opening Environment And Baseline Agent
Reinforcement Learning (RL) has brought forth ideas of autonomous robots...
08/05/2019 ∙ by Yusuke Urakami, et al. ∙
35
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Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method
Classical Principal Component Analysis (PCA) approximates data in terms ...
07/24/2019 ∙ by Guihong Wan, et al. ∙
34
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A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
The success of deep learning has been witnessed as a promising technique...
08/01/2019 ∙ by Pengyi Zhang, et al. ∙
34
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Transferability of Spectral Graph Convolutional Neural Networks
This paper focuses on spectral graph convolutional neural networks (Conv...
07/30/2019 ∙ by Ron Levie, et al. ∙
32
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Benchmarking TPU, GPU, and CPU Platforms for Deep Learning
Training deep learning models is compute-intensive and there is an indus...
07/24/2019 ∙ by Gu-Yeon Wei, et al. ∙
31
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Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance Propagation
Convolutional Neural Networks (CNN) have become state-of-the-art in the ...
08/06/2019 ∙ by Brian Kenji Iwana, et al. ∙
30
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