Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation

Related tags

Deep LearningVOTEN
Overview

Configurations

  • Change HOME_PATH in CONFIG.py as the current path

Data Prepare

CENSINCOME

  • Download data
  • Put census-income.data and census-income.test in Data/Downloads/census-income
  • Run DataProcess/CENSINCOME/process.py

COVTYPE

  • Download data
  • Put covtype.data in Data/Downloads/COVTYPE/
  • Run DataProcess/COVTYPE/process.py

IJCAI18X

  • Download data
  • Generate train.csv and test.csv with xgboost1.py
  • Put train.csv and test.cvs in Data/RawData/IJCAI18X
  • Run DataProcess/IJCAI18X/process.py

KDDCUP19

  • Download data
  • Put train_queries.csv, train_plans.csv, train_clicks.csv, profiles.csv in Data/Downloads/KDDCUP19P1
  • Run DataProcess/KDC/process.py

Training

Train and save the model

  • Use the scripts in Train/{DATASET}/
  • Will train the model and save the model in Data/Saved/{DATASET}/[VOTERS or DNN]/model

Explanation

Generate intermediate results of voting analysis

  • Run SaveInter/save.py

Visualizations for explanation

  • Run E1 to E6 in Explain/analysis, the visualizations will be saved in Explain/out

Demo system for local/global decision path visualization

  • Open the path of the django project in Site/
  • Start the server: python manage.py runserver 0.0.0.0:8000
  • Use the system in browser with URL: 127.0.0.1:8000/{global/local}/{covtyp/kdc/ijcai/cens}

Citation

If you use this code, please cite our paper "Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation" published in NeurIPS 2021.

Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss (ATVGnet)

Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss (ATVGnet) By Lele Chen , Ross K Maddox, Zhiyao Duan, Chenliang Xu. Unive

Lele Chen 218 Dec 27, 2022
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral)

ILVR + ADM This is the implementation of ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (ICCV 2021 Oral). This repository is h

Jooyoung Choi 225 Dec 28, 2022
Official Pytorch implementation of "Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes", CVPR 2022

Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes / 3DCrowdNet News 💪 3DCrowdNet achieves the state-of-the-art accuracy on 3D

Hongsuk Choi 113 Dec 21, 2022
Semantically Contrastive Learning for Low-light Image Enhancement

Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig

48 Dec 16, 2022
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.

Documentation: https://mmgeneration.readthedocs.io/ Introduction English | 简体中文 MMGeneration is a powerful toolkit for generative models, especially f

OpenMMLab 1.3k Dec 29, 2022
Emulation and Feedback Fuzzing of Firmware with Memory Sanitization

BaseSAFE This repository contains the BaseSAFE Rust APIs, introduced by "BaseSAFE: Baseband SAnitized Fuzzing through Emulation". The example/ directo

Security in Telecommunications 138 Dec 16, 2022
Place holder for HOPE: a human-centric and task-oriented MT evaluation framework using professional post-editing

HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation Place holder for dat

Lifeng Han 1 Apr 25, 2022
Pytorch implementation of VAEs for heterogeneous likelihoods.

Heterogeneous VAEs Beware: This repository is under construction 🛠️ Pytorch implementation of different VAE models to model heterogeneous data. Here,

Adrián Javaloy 35 Nov 29, 2022
disentanglement_lib is an open-source library for research on learning disentangled representations.

disentanglement_lib disentanglement_lib is an open-source library for research on learning disentangled representation. It supports a variety of diffe

Google Research 1.3k Dec 28, 2022
Official PyTorch Implementation of Convolutional Hough Matching Networks, CVPR 2021 (oral)

Convolutional Hough Matching Networks This is the implementation of the paper "Convolutional Hough Matching Network" by J. Min and M. Cho. Implemented

Juhong Min 70 Nov 22, 2022
"Inductive Entity Representations from Text via Link Prediction" @ The Web Conference 2021

Inductive entity representations from text via link prediction This repository contains the code used for the experiments in the paper "Inductive enti

Daniel Daza 45 Jan 09, 2023
A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN

A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN Please follow Faster R-CNN and DAF to complete the environment confi

2 Jan 12, 2022
A Jinja extension (compatible with Flask and other frameworks) to compile and/or compress your assets.

A Jinja extension (compatible with Flask and other frameworks) to compile and/or compress your assets.

Jayson Reis 94 Nov 21, 2022
UIUCTF 2021 Public Challenge Repository

UIUCTF-2021-Public UIUCTF 2021 Public Challenge Repository Notes: every challenge folder contains a challenge.yml file in the format for ctfcli, CTFd'

SIGPwny 15 Nov 03, 2022
Evolving neural network parameters in JAX.

Evolving Neural Networks in JAX This repository holds code displaying techniques for applying evolutionary network training strategies in JAX. Each sc

Trevor Thackston 6 Feb 12, 2022
MLPs for Vision and Langauge Modeling (Coming Soon)

MLP Architectures for Vision-and-Language Modeling: An Empirical Study MLP Architectures for Vision-and-Language Modeling: An Empirical Study (Code wi

Yixin Nie 27 May 09, 2022
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder

Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many

Eashan Adhikarla 4 Dec 25, 2022
Train Scene Graph Generation for Visual Genome and GQA in PyTorch >= 1.2 with improved zero and few-shot generalization.

Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr

Boris Knyazev 93 Dec 28, 2022
Analyzing basic network responses to novel classes

novelty-detection Analyzing how AlexNet responds to novel classes with varying degrees of similarity to pretrained classes from ImageNet. If you find

Noam Eshed 34 Oct 02, 2022
unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier"

SquarePlus (Pytorch implement) unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier" SquarePlus Squareplus is a Softplus-L

SeeFun 3 Dec 29, 2021