Eisen: a python package for solid deep learning
- URL: http://arxiv.org/abs/2004.02747v1
- Date: Wed, 18 Mar 2020 14:07:54 GMT
- Title: Eisen: a python package for solid deep learning
- Authors: Frank Mancolo
- Abstract summary: Eisen is an open source python package making the implementation of deep learning methods easy.
It is specifically tailored to medical image analysis and computer vision tasks.
It follows the same architecture of other packages belonging to the PyTorch ecosystem.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Eisen is an open source python package making the implementation of deep
learning methods easy. It is specifically tailored to medical image analysis
and computer vision tasks, but its flexibility allows extension to any
application. Eisen is based on PyTorch and it follows the same architecture of
other packages belonging to the PyTorch ecosystem. This simplifies its use and
allows it to be compatible with modules provided by other packages. Eisen
implements multiple dataset loading methods, I/O for various data formats, data
manipulation and transformation, full implementation of training, validation
and test loops, implementation of losses and network architectures, automatic
export of training artifacts, summaries and logs, visual experiment building,
command line interface and more. Furthermore, it is open to user contributions
by the community. Documentation, examples and code can be downloaded from
http://eisen.ai.
Related papers
- Comgra: A Tool for Analyzing and Debugging Neural Networks [35.89730807984949]
We introduce comgra, an open source python library for use with PyTorch.
Comgra extracts data about the internal activations of a model and organizes it in a GUI.
It can show both summary statistics and individual data points, compare early and late stages of training, focus on individual samples of interest, and visualize the flow of the gradient through the network.
arXiv Detail & Related papers (2024-07-31T14:57:23Z) - pyvene: A Library for Understanding and Improving PyTorch Models via
Interventions [79.72930339711478]
$textbfpyvene$ is an open-source library that supports customizable interventions on a range of different PyTorch modules.
We show how $textbfpyvene$ provides a unified framework for performing interventions on neural models and sharing the intervened upon models with others.
arXiv Detail & Related papers (2024-03-12T16:46:54Z) - scikit-fda: A Python Package for Functional Data Analysis [0.0]
scikit-fda is a Python package for Functional Data Analysis (FDA)
It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data.
arXiv Detail & Related papers (2022-11-04T16:34:03Z) - Torchhd: An Open Source Python Library to Support Research on
Hyperdimensional Computing and Vector Symbolic Architectures [99.70485761868193]
We present Torchhd, a high-performance open source Python library for HD/VSA.
Torchhd seeks to make HD/VSA more accessible and serves as an efficient foundation for further research and application development.
arXiv Detail & Related papers (2022-05-18T20:34:25Z) - DADApy: Distance-based Analysis of DAta-manifolds in Python [51.37841707191944]
DADApy is a python software package for analysing and characterising high-dimensional data.
It provides methods for estimating the intrinsic dimension and the probability density, for performing density-based clustering and for comparing different distance metrics.
arXiv Detail & Related papers (2022-05-04T08:41:59Z) - PyTorchVideo: A Deep Learning Library for Video Understanding [71.89124881732015]
PyTorchVideo is an open-source deep-learning library for video understanding tasks.
It covers a full stack of video understanding tools including multimodal data loading, transformations, and models.
The library is based on PyTorch and can be used by any training framework.
arXiv Detail & Related papers (2021-11-18T18:59:58Z) - pymia: A Python package for data handling and evaluation in deep
learning-based medical image analysis [0.9176056742068814]
pymia is an open-source Python package for data handling and evaluation in medical image analysis.
The package is highly flexible, allows for fast prototyping, and reduces the burden of implementing data handling routines.
pymia was successfully used in a variety of research projects for segmentation, reconstruction, and regression.
arXiv Detail & Related papers (2020-10-07T20:25:52Z) - TorchKGE: Knowledge Graph Embedding in Python and PyTorch [0.0]
TorchKGE is a Python module for knowledge graph (KG) embedding relying solely on PyTorch.
It features a KG data structure, simple model interfaces and modules for negative sampling and model evaluation.
arXiv Detail & Related papers (2020-09-07T09:21:34Z) - mvlearn: Multiview Machine Learning in Python [103.55817158943866]
mvlearn is a Python library which implements the leading multiview machine learning methods.
The package can be installed from Python Package Index (PyPI) and the conda package manager.
arXiv Detail & Related papers (2020-05-25T02:35:35Z) - TorchIO: A Python library for efficient loading, preprocessing,
augmentation and patch-based sampling of medical images in deep learning [68.8204255655161]
We present TorchIO, an open-source Python library to enable efficient loading, preprocessing, augmentation and patch-based sampling of medical images for deep learning.
TorchIO follows the style of PyTorch and integrates standard medical image processing libraries to efficiently process images during training of neural networks.
It includes a command-line interface which allows users to apply transforms to image files without using Python.
arXiv Detail & Related papers (2020-03-09T13:36:16Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.