31页PPT概述:图神经网络表达能力有多强?

AI科技大本营 2019-02-19 10:53
近年来,图神经网络的研究正成为深度学习领域的热点。
14 0 0

清华大学孙茂松课题组:《图神经网络:方法与应用》综述论文,20页pdf

专知 2018-12-25 11:39
全面总结了最新图神经网络的模型,应用和未来研究方向,是研究该领域的重要的参阅资料
444 0 1

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks

辉仔 2018-01-10 10:21
We present an integrated framework for using Convolutional Networks for classification, localization and detection. We show how a multiscale and sliding window approach can be efficiently implemented

Learning Transferable Architectures for Scalable Image Recognition

jixiaohui 2018-01-10 15:36
Developing neural network image classification models often requires significant architecture engineering. In this paper, we attempt to automate this engineering process by learning the model architec

深度学习12大常见问题解答(附答案)

no_speaking 2018-06-10 23:37
阿尔法狗让深度学习登上了数据科学世界的巅峰。深度学习成为了当今最热门的话题之一,但对于大多数人来说,这是一个陌生而又神秘的学科。很多人认为,深度学习就是包括了大量的数学和统计知识。本文列举了常见的12个深度学习的问题。
522 0 0

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

辉仔 2018-01-10 11:09
In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications. Comparatively, unsupervised learning with CNNs has received less attenti

Going Deeper with Convolutions

辉仔 2018-01-10 11:12
We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Sca

Learning to Segment Every Thing

dwSun 2018-01-15 20:39
Existing methods for object instance segmentation require all training instances to be labeled with segmentation masks. This requirement makes it expensive to annotate new categories and has restricte

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation

dwSun 2018-02-06 17:25
In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of diffe

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

jixiaohui 2018-01-10 11:37
Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. One example is the Inception architecture that has been shown to achieve ve
关注微信公众号