首页/数据集/Neuro-Visualizer: An Auto-encoder-based Loss Landscape Visualization Method

Neuro-Visualizer: An Auto-encoder-based Loss Landscape Visualization Method

NIAID Data Ecosystem2026-05-01 收录

损失景观可视化

深度学习可解释性

数据链接：

https://zenodo.org/record/8263892 数据链接链接失效反馈

官方服务：

资源简介：

This is the data needed to run the code found in: https://anonymous.4open.science/r/NeuroVisualizer-FDD6 - Input trajectory model data: trajectories_v2.zip - Trained Neuro-Visualizers and results: saved_models_v2.zip - Other important auxiliary data: data_v2.zip

应用场景：

创建时间：

2023-08-19

相关数据集

Synthetic Cell Dataset

细胞图像分析

深度学习可解释性

该数据集是一个按需生成的合成数据集，包含了具有不同特征的细胞图像以及相应的真实热力图，用于评估深度神经网络中的可解释性方法。该数据集包含10类细胞，这些细胞在形状、颜色和背景上存在变化。每个真实热力图旨在突出显示区分所有类别的特征，并根据需要可进行调整。规模上，数据集总共包含6400个训练样本，1600个验证样本以及1600个评估样本。任务是对使用生成的热力图在深度神经网络中评估可解释性方法。

arXiv150

Classification performance(%) at each layer where the desk-globe class is positive.

分类模型层级分析

深度学习可解释性

Classification performance(%) at each layer where the desk-globe class is positive.

Figshare2020-09-17 更新30

Relevance data for: Cross-Domain Transfer Learning Strategy Enhances Interpretability of Deep Learning Model Explanations

心电图检测

深度学习可解释性

This dataset contains pre-computed relevance data extracted from deep learning models trained for atrial fibrillation (AF) detection in 10-second single-lead Einthoven lead II ECGs. Relevance values w

Zenodo2026-04-13 更新10

Replication Data for: Relevance propagation Results with the Caffe Network and Bag of Words classifiers as used in \"On Pixel-wise Explanations for Non-Linear Classifier Decisions by Layer-wise Relevance Propaganda\"

深度学习可解释性

图像分类解释

This data set contains all the example images used in the manuscript \"On Pixel-wise Explanations for Non-Linear Classifier Decisions by Layer-wise Relevance Propaganda\" submitted to PLOS ONE (PONE-D

DataONE2018-09-07 更新50

DeepAnnotation: A novel interpretable deep learning-based genomic selection model that integrates comprehensive functional annotations

基因组选择

深度学习可解释性

1. Update package, example dataset, and demo code of DeepAnnotation 2. Update the transformed genotype data, the phenotype data, the comprehensive functional annotation data for Duroc prepared by RNAf

Zenodo2025-03-22 更新10