Research shows Google collects 20x more data from Android than Apple collects from iOS. Block this non-consensual telemetry using pihole blocklists.

Last update: Jan 09, 2023

Overview

pihole-antitelemetry

Research shows Google collects 20x more data from Android than Apple collects from iOS. Block both using these pihole lists.

Project Goals and FAQ

The purpose and goals of this blocklist are outliined in the FAQ

The lists

For a list of domains that should not break anything, use telemetry-domains.txt.

If you want to also block domains that are not well-tested, add telemetry-domains_beta.txt to the list.

Domains that are known to break user-facing services or apps are moved to telemetry-domains_borked.txt for use at your own risk.

These lists are maintained with help from the community. Any efforts to help sort domains into the correct blocklists will help others better block non-consensual telemetry.

Existing lists

Owner

Adrian Edwards

GitHub Repository

Code repository for the paper "Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation" with instructions to reproduce the results.

Doubly Trained Neural Machine Translation System for Adversarial Attack and Data Augmentation Languages Experimented: Data Overview: Source Target Tra

1 Aug 18, 2022

WeakVRD-Captioning - Implementation of paper Improving Image Captioning with Better Use of Caption

30 Oct 28, 2022

This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"

ICCV Workshop 2021 VTGAN This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"

25 Dec 08, 2022

An unopinionated replacement for PyTorch's Dataset and ImageFolder, that handles Tar archives

Simple Tar Dataset An unopinionated replacement for PyTorch's Dataset and ImageFolder classes, for datasets stored as uncompressed Tar archives. Just

47 Dec 20, 2022

This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.

This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their

8 May 22, 2022

EfficientMPC - Efficient Model Predictive Control Implementation

efficientMPC Efficient Model Predictive Control Implementation The original algo

8 Dec 04, 2022

Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

243 Dec 26, 2022

Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022.

Jadena Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022. arXiv

13 Nov 29, 2022

Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images

BlockGAN Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images BlockGAN: Learning 3D Object-aware Scene Rep

41 May 18, 2022

Code for ViTAS_Vision Transformer Architecture Search

Vision Transformer Architecture Search This repository open source the code for ViTAS: Vision Transformer Architecture Search. ViTAS aims to search fo

46 Dec 17, 2022

GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms

GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms Trying to publish a new machine learning model and can't write a decent title for your pa

264 Nov 08, 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

113 Dec 21, 2022

The Official PyTorch Implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 spotlight paper)

Official PyTorch implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 Spotlight Paper) Zhisheng

45 Dec 26, 2022

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage

5.7k Jan 09, 2023