Convolutional Neural Networks For Sentence
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Deep Learning Based Text Classification: A Comprehensive ...
arxiv.orgincluding recurrent neural networks (RNNs), convolutional neural networks (CNNs), attention, Transformers, Capsule Nets, and so on. The contributions of this paper can be summarized as follows: ... the task of measuring the semantic similarity of a sentence pair indicating how likely one sentence is a paraphrase of the other. 1.2 Paper Structure
MSR-VTT: A Large Video Description Dataset for Bridging ...
www.microsoft.comthe input to the long-term recurrent convolutional networks to output sentences [7]. In [35], Venugopalan et al. design an encoder-decoder neural network to generate description-s. By mean pooling, the features over all frames can be represented by one single vector, which is the input of the RNN. Compared to mean-pooling, Li et al. propose to u-
Learning Convolutional Neural Networks for Graphs
proceedings.mlr.pressLearning Convolutional Neural Networks for Graphs 3. Background We provide a brief introduction to the required background in convolutional networks and graph theory. 3.1. Convolutional Neural Networks CNNs were inspired by earlier work that showed that the visual cortex in animals contains complex arrangements
Show, Attend and Tell: Neural Image CaptionGeneration …
proceedings.mlr.pressanalogous to “translating” an image to a sentence. The first approach to using neural networks for caption gen-eration was proposed byKiros et al.(2014a) who used a multimodal log-bilinear model that was biased by features from the image. This work was later followed byKiros et al.(2014b) whose method was designed to explicitly al-
Generative Adversarial Text to Image Synthesis
proceedings.mlr.pressGenerative adversarial networks (Goodfellow et al.,2014) have also benefited from convolutional decoder networks, for the generator network module.Denton et al.(2015) used a Laplacian pyramid of adversarial generator and dis-criminators to synthesize images at multiple resolutions. This work generated compelling high-resolution images