XDeep: An Interpretation Tool for Deep Neural Networks

11/04/2019
by   Fan Yang, et al.
0

XDeep is an open-source Python package developed to interpret deep models for both practitioners and researchers. Overall, XDeep takes a trained deep neural network (DNN) as the input, and generates relevant interpretations as the output with the post-hoc manner. From the functionality perspective, XDeep integrates a wide range of interpretation algorithms from the state-of-the-arts, covering different types of methodologies, and is capable of providing both local explanation and global explanation for DNN when interpreting model behaviours. With the well-documented API designed in XDeep, end-users can easily obtain the interpretations for their deep models at hand with several lines of codes, and compare the results among different algorithms. XDeep is generally compatible with Python 3, and can be installed through Python Package Index (PyPI). The source codes are available at: https://github.com/datamllab/xdeep.

READ FULL TEXT

page 4

page 5

research
10/27/2019

Neural Network Distiller: A Python Package For DNN Compression Research

This paper presents the philosophy, design and feature-set of Neural Net...
research
01/12/2022

PyHHMM: A Python Library for Heterogeneous Hidden Markov Models

We introduce PyHHMM, an object-oriented open-source Python implementatio...
research
09/19/2019

InterpretML: A Unified Framework for Machine Learning Interpretability

InterpretML is an open-source Python package which exposes machine learn...
research
06/19/2023

Interpreting Deep Neural Networks with the Package innsight

The R package innsight offers a general toolbox for revealing variable-w...
research
04/26/2023

HiQ – A Declarative, Non-intrusive, Dynamic and Transparent Observability and Optimization System

This paper proposes a non-intrusive, declarative, dynamic and transparen...
research
03/10/2020

An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs

We present Karate Club a Python framework combining more than 30 state-o...
research
12/03/2018

Sensitivity based Neural Networks Explanations

Although neural networks can achieve very high predictive performance on...

Please sign up or login with your details

Forgot password? Click here to reset