Data-to-Text Generation (D2T NLG) can be described as Natural Language Generation from structured input. Unlike other NLG tasks such as, Machine Translation or Question Answering (also referred as Text-to-Text Generation or T2T NLG) where requirement is to generate textual output using some ...
Expertise: Data Management, Screening results analysis, Statistical programming, Medicinal Chemistry evaluation, Hit-to-Lead Musheng Zeng Sun Yat-sen University, ChinaExpertise: Cancer, Virology, Translational Medicine, Next-generation sequencing, Gene regulation Fan Zhang University of Electronic Science ...
Systems of data replication have also displayed some security weaknesses with respect to the generation of multiple copies, data governance, and policy. These policies define the data that are stored, analyzed, and accessed. They also determine the relevance of these data. To process unstructured ...
Evidence from a national survey of faculty. To identify the prevalence and determinants of data-withholding behaviors among academic life scientists.Mailed survey of 3394 life science faculty in the ... Blumenthal,E G,Campbell,... - 《Jama the Journal of the American Medical Association》 被引...
A data sharing system refers to a system where multiple machines or processes can access the same database or stable storage devices, enabling the synchronization of access to shared data. It allows for replication of the server but not the resource, and is commonly used in clustered systems an...
aThe survey data showed that human compositions are still preferred, but also that 72 percent of respondents either could not distinguish between a human and computer composition, or preferred a computer composition over a human composition. Dividing the musicgeneration process into several operations re...
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augmentation summar
Researchers may find it hard to select appropriate generation methods for different scenarios. This survey aims to bridge this gap. The sources of articles that are taken into consideration are top journals such as those published by IEEE, Springer, Elsevier, etc., and proceedings of top ...
ktext - Utilities for pre-processing text for deep learning in Keras. textgenrnn - Ready-to-use LSTM for text generation. ctrl - Text generation. Neural network and deep learning frameworks OpenMMLab - Framework for segmentation, classification and lots of other computer vision tasks. caffe - ...
Unit Test Case Generation with Transformers Microsoft 2021 Audio Improving On-Device Speech Recognition with VoiceFilter-Lite (Paper)Google 2020 The Machine Learning Behind Hum to Search Google 2020 Privacy-preserving Machine Learning Federated Learning: Collaborative Machine Learning without Centralized Traini...