vu1seek Goto Github PK

demo-sso

A simple example web application integrating the Jolocom library for authentication.

denoising-diffusion-pytorch

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

dev_training

Resources related to developer training presentations

dialogstudio

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection and Instruction-Aware Models for Conversational AI

dictionary-of-pentesting

Dictionary collection project such as Pentesing, Fuzzing, Bruteforce and BugBounty. 渗透测试、SRC漏洞挖掘、爆破、Fuzzing等字典收集项目。

diffpure

A new adversarial purification method that uses the forward and reverse processes of diffusion models to remove adversarial perturbations.

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

diffusion_models-minimal_standalone_example

Minimal standalone example of diffusion model

discovery

Watson Discovery service docs

distributed-tensorflow-guide

Distributed TensorFlow basics and examples of training algorithms

dnntune

A DNN tuning framework for mobile devices

docker-cheat-sheet

Docker Cheat Sheet

docker-nheqminer-cuda

CUDA capable docker image of nheqminer (zcash/equihash miner)

docs

General musings

dolly

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

doppler-android

Motion sensing using the doppler effect, for android

down

dpml-benchmark

This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.

draggan

Code for DragGAN (SIGGRAPH 2023)

droidlibindy

An Android Studio project to test libindy on Android

droo

Deep Reinforcement Learning for Online Computation Offloading in Wireless Powered Mobile-Edge Computing Networks

dynamic-time-warping

A Dynamic Time Warping (DTW) implementation on Android.

easyinstruct

An easy-to-use framework to instruct Large Language Models.

edge-intelligence

随着移动云计算和边缘计算的快速发展，以及人工智能的广泛应用，产生了边缘智能(Edge Intelligence)的概念。深度神经网络(例如CNN)已被广泛应用于移动智能应用程序中，但是移动设备有限的存储和计算资源无法满足深度神经网络计算的需求。神经网络压缩与加速技术可以加速神经网络的计算，例如剪枝、量化、卷积核分解等。但是这些技术在实际应用非常复杂，并且可能导致模型精度的下降。在移动云计算或边缘计算中，任务卸载技术可以突破移动终端的资源限制，减轻移动设备的计算负载并提高任务处理效率。通过任务卸载技术优化深度神经网络成为边缘智能研究中的新方向。Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge这篇文章提出了协同推断的**，将深度神经网络进行分区，一部分层在移动端计算，而另一部分在云端计算。根据硬件平台、无线网络以及服务器负载等因素实现动态分区，降低时延以及能耗。本项目给出了边缘智能方面的相关论文，并且给出了一个Python语言实现的卷积神经网络协同推断实验平台。关键词：边缘智能(Edge Intelligence)，计算卸载(Computing Offloading)，CNN模型分区(CNN Partition)，协同推断(Collaborative Inference)，移动云计算(Mobile Cloud Computing)

enerf

Implementation of E-NeRF: Neural Radiance Fields from a Moving Event Camera (https://arxiv.org/abs/2208.11300). Simulated dataset: https://vision.in.tum.de/research/enerf

ethereum-bootstrap

Starter kit to ethereum private chain.

ethereumbook

Mastering Ethereum, by Andreas M. Antonopoulos, Gavin Wood

evaluatingdpml

excessive-invariance

Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"

experimental-fall-detector-android-app

Experimental Fall Detector Android App