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Category: 人工智能 View all
- Distributed Representations of Words and Phrases and their Compositionality 人工智能
全球高被引研究（被引 18,054 次，发表于 2013）。 The recently introduced continuous Skip-gram model is an efficient method for learning high-quality distributed…
- Deep learning in neural networks: An overview 人工智能
全球高被引研究（被引 18,183 次，发表于 2014）。 该论文提供官方开放获取 PDF 全文，可直接下载阅读。
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks 人工智能
全球高被引研究（被引 18,226 次，发表于 2015）。 State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations…
- Regularization and Variable Selection Via the Elastic Net 人工智能
全球高被引研究（被引 21,396 次，发表于 2005）。 Summary We propose the elastic net, a new regularization and variable selection method. Real world data and a s…
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale 人工智能
全球高被引研究（被引 21,934 次，发表于 2020）。 While the Transformer architecture has become the de-facto standard for natural language processing tasks, its …
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 人工智能
全球高被引研究（被引 24,393 次，发表于 2015）。 Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes d…
- Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation 人工智能
全球高被引研究（被引 24,896 次，发表于 2014）。 Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua …
- Random sample consensus 人工智能
全球高被引研究（被引 25,759 次，发表于 1981）。 A new paradigm, Random Sample Consensus (RANSAC), for fitting a model to experimental data is introduced. RANSA…
- Neural Networks: A Comprehensive Foundation 人工智能
全球高被引研究（被引 29,842 次，发表于 1998）。 From the Publisher: This book represents the most comprehensive treatment available of neural networks from an…
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