recusant7 Goto Github PK

anomalyllm

ans

Autodidactic Neurosurgeon Collaborative Deep Inference for Mobile Edge Intelligence via Online Learning

arcface-pytorch

awesome-ai-for-time-series-papers

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

awesome-ml-demos-with-ios

The challenge projects for Inferencing machine learning models on iOS

cdc_compression

codebase for Lossy Image Compression with Conditional Diffusion Models

clip

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

contrastive-clustering

Code for the paper "Contrastive Clustering" (AAAI 2021)

crnet

Channel Reconstruction Network implemented in PyTorch

dcrnet

The offical repo for the paper entitled "Dilated Convolution based CSI Feedback Compression for Massive MIMO System".

deep-jscc-pytorch

A implement of Deep JSCC for wireless image transmission by PyTorch

deepi2p

DeepI2P: Image-to-Point Cloud Registration via Deep Classification. CVPR 2021

denoisecompression

[ECCV2022] Optimizing Image Compression via Joint Learning with Denoising

diffusion-low-light

Official pytorch implementation for "Low-light Image Enhancement with Wavelet-based Diffusion Models"

drlnd-project-3

Implementation of project 3 for Udacity's Deep Reinforcement Learning Nanodegree

dynamic_jscc

Codes for "Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control", ICASSP 2022

ecct

Error Correction Code Transformer

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)

english-writing

Enhance Your English Writing for Science Research 写论文英语素材

feel

part code of paper entitled "battery-constrained federated edge learning in uav-enabled iot for b5g/6g networks"

fl_pytorch

A simple simulation of Federated learning

gan-inversion

[TPAMI 2022] GAN Inversion: A Survey

gan_secom

Channel-aware GAN Inversion for Semantic Communication

gesco

Offcial PyTorch repository for the paper "Generative Semantic Communication: Diffusion Models Beyond Bit Recovery"

guided-diffusion

hi-diff

PyTorch code for our NeurIPS 2023 paper "Hierarchical Integration Diffusion Model for Realistic Image Deblurring"

homepage

inade

Implementation of Diverse Semantic Image Synthesis via Probability Distribution Modeling (CVPR 2021)

interview_python

关于Python的面试题

latex_paper_writing

Tips for Writing a Research Paper using LaTeX