منابع مشابه
Question Answering on SQuAD
In this project, we exploit several deep learning architectures in Question Answering field, based on the newly released Stanford Question Answering dataset (SQuAD)[7]. We introduce a multi-stage process that encodes context paragraphs at different levels of granularity, uses co-attention mechanism to fuse representations of questions and context paragraphs, and finally decodes the co-attention...
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One important task in Natural Language Understanding is Reading Comprehension. Given a piece of text, we want to be able to answer any relevant questions. Using Stanford Question Answering Dataset(SQuAD), which is a new reading comprehension dataset consisting of 100,000+ questions posed by crowdworkers on a set of Wikipedia articles, we built a reading comprehension model that attains 75.2% F1...
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The Firing Squad Synchronization Problem (FSSP) is one of the best-studied problems for Cellular Automata (CA) and is part of many more sophisticated algorithms. Solutions for it such as the one from Mazoyer or Gerken use travelling signals, a basic technique of CA algorithms. Hence in addition to their importance, they represent typical CA algorithms. Beside the interest in their bandwidth fol...
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ژورنال
عنوان ژورنال: Mechanical Engineering
سال: 2008
ISSN: 0025-6501,1943-5649
DOI: 10.1115/1.2008-may-4