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...
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.
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
[Boost] tiny-dnn - A header only, dependency-free deep learning framework in C++11. [BSD] Veles - Distributed platform for rapid Deep learning application development. [Apache] Kaldi - Toolkit for speech recognition. [Apache]Asynchronous Event Loop...
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Machine Learning Framework: Eager mode framework: e.g.: PyTorch, JAX 命令式运行定义方法(imperative define-by-run) approach 机器学习模型表达为每次运行时所需的代码learning model is represented as code that is executed each time one wants to run the model ...
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Here we present RefHiC, a deep learning framework that utilizes a reference panel to guide the annotation of topological structure from a given study sample. In contrast, existing topological structure detection algorithms are study-sample based (i.e., reference-free) detectors and hence their abil...