L2X - Code for replicating the experiments in the paper Learning to Explain: An Information-Theoretic Perspective on Model Interpretation.

Overview

L2X

Code for replicating the experiments in the paper Learning to Explain: An Information-Theoretic Perspective on Model Interpretation at ICML 2018, by Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan.

Dependencies

The code for L2X runs with Python and requires Tensorflow of version 1.2.1 or higher and Keras of version 2.0 or higher. Please pip install the following packages:

  • numpy
  • tensorflow
  • keras
  • pandas
  • nltk

Or you may run the following and in shell to install the required packages:

git clone https://github.com/Jianbo-Lab/L2X
cd L2X
sudo pip install -r requirements.txt

See README.md in respective folders for details.

Citation

If you use this code for your research, please cite our paper:

@arxiv{chen2018learning,
title = {Learning to Explain: An Information-Theoretic Perspective on Model Interpretation},
author = {Chen, Jianbo and Song, Le and Wainwright, Martin J and Jordan, Michael I}, 
journal={arXiv preprint arXiv:1802.07814}, 
year = {2018}  
}
Owner
Jianbo Chen
Quantitative researcher at Citadel Securities; PhD in Statistics at UC Berkeley working with Michael I. Jordan and Martin J. Wainwright.
Jianbo Chen
Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University

Contrastive Explanation (Foil Trees) Contrastive and counterfactual explanations for machine learning (ML) Marcel Robeer (2018-2020), TNO/Utrecht Univ

M.J. Robeer 41 Aug 29, 2022
A game theoretic approach to explain the output of any machine learning model.

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

Scott Lundberg 18.3k Jan 08, 2023
Convolutional neural network visualization techniques implemented in PyTorch.

This repository contains a number of convolutional neural network visualization techniques implemented in PyTorch.

1 Nov 06, 2021
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.

Jacob Gildenblat 6.5k Jan 01, 2023
Implementation of linear CorEx and temporal CorEx.

Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx

Hrayr Harutyunyan 34 Nov 15, 2022
A collection of infrastructure and tools for research in neural network interpretability.

Lucid Lucid is a collection of infrastructure and tools for research in neural network interpretability. We're not currently supporting tensorflow 2!

4.5k Jan 07, 2023
Interpretability and explainability of data and machine learning models

AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase

1.2k Dec 29, 2022
Model analysis tools for TensorFlow

TensorFlow Model Analysis TensorFlow Model Analysis (TFMA) is a library for evaluating TensorFlow models. It allows users to evaluate their models on

1.2k Dec 26, 2022
A collection of research papers and software related to explainability in graph machine learning.

A collection of research papers and software related to explainability in graph machine learning.

AstraZeneca 1.9k Dec 26, 2022
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

Jesse Vig 4.7k Jan 01, 2023
PyTorch implementation of DeepDream algorithm

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br

121 Nov 05, 2022
An Empirical Review of Optimization Techniques for Quantum Variational Circuits

QVC Optimizer Review Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits". Each of the python files ca

Owen Lockwood 5 Jun 28, 2022
treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.

TreeInterpreter Package for interpreting scikit-learn's decision tree and random forest predictions. Allows decomposing each prediction into bias and

Ando Saabas 720 Dec 22, 2022
A ultra-lightweight 3D renderer of the Tensorflow/Keras neural network architectures

A ultra-lightweight 3D renderer of the Tensorflow/Keras neural network architectures

Souvik Pratiher 16 Nov 17, 2021
Visualizer for neural network, deep learning, and machine learning models

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,

Lutz Roeder 20.9k Dec 28, 2022
👋ðŸĶŠ Xplique is a Python toolkit dedicated to explainability, currently based on Tensorflow.

👋ðŸĶŠ Xplique is a Python toolkit dedicated to explainability, currently based on Tensorflow.

DEEL 343 Jan 02, 2023
Interactive convnet features visualization for Keras

Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis

Keplr 1.7k Dec 21, 2022
Visualization toolkit for neural networks in PyTorch! Demo -->

FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The

Misa Ogura 692 Dec 29, 2022
Code for visualizing the loss landscape of neural nets

Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer

Tom Goldstein 2.2k Dec 30, 2022
TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, Korean, Chinese, German and Easy to adapt for other languages)

ðŸĪŠ TensorFlowTTS provides real-time state-of-the-art speech synthesis architectures such as Tacotron-2, Melgan, Multiband-Melgan, FastSpeech, FastSpeech2 based-on TensorFlow 2. With Tensorflow 2, we c

3k Jan 04, 2023