2022年6月15日,岳峰课题组在Science Advances上发表了题为EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps的工作。该项工作基于深度学习和集成学习策略...
Abstract 背景:目前对cross-framework conversion中的inconsistencies和security bugs的研究少有 本文:TensorScope Github:https://github.com/tensorscopepro/Tensorscope Task: test cross-frame APIs in Machine Learning Libraries Method: 1. Differential Testing among Machine Learning Libraries 2. joint constraint an...
deep learning frameworkmultiple feature setssingle-cell Hi-CSingle-cell high-throughput chromosome conformation capture (Hi-C) technology enables capturing chromosomal spatial structure information at the cellular level. However, to effectively investigate changes in chromosomal structure across different cell ...
Wang X, Luan Y, Yue F. EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps[J]. Science Advances, 2022, 8(24): eabn9215.
参考文献 Wang X, Luan Y, Yue F. EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps[J]. Science Advances, 2022, 8(24): eabn9215.
A deep-learning framework for predicting a full range of structural variations from bulk and single-cell contact maps - XiaoTaoWang/EagleC
vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers - ai-techsystems/deepC
In this work, 123 COVID-CheXNet: hybrid deep learning framework for identifying COVID-19 virus in chest X-rays… 2663 the transfer learning strategy to pre-trained ResNet34 and HRNet model was applied for several reasons, including: (1) to avoid the overfitting problem due to unavailability...
Moteur de transformation de seconde génération Le moteur de transformation de seconde génération fait appel à une version personnalisée de la technologie Blackwell Tensor Core combinée aux innovations de la bibliothèque logicielle NVIDIA® TensorRT™-LLM et du framework NeMo™ pour accélérer...
介绍完这些内容之后,很多人自然会对优化的最为广泛的应用——深度学习(deep learning)感兴趣。的确,无论是处理计算机视觉(Computer Vision,CV)相关问题的卷积神经网络(Convolutional Neural Network,CNN),还是处理自然语言处理(Natural Language Processing,NLP)相关问题的循环神经网络(Recurrent Neural Network,RNN),它们的...