Stars
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
[ICRA 2023] V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perception
A Distributed Platform Approach to Cooperative Perception based on Celluar-V2X Communication
[ECCV2022] Official Implementation of paper "V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer"
This repository is a paper digest of recent advances in collaborative / cooperative / multi-agent perception for V2I / V2V / V2X autonomous driving scenario.
Spectrum sharing in vehicular networks based on multi-agent reinforcement learning, IEEE Journal on Selected Areas in Communications
Reconfigurable Adaptive Array Beamforming by Antenna Selection
MUSIC + MMSE for adaptive antenna array
simulation of an Adaptive Beamforming Radar using MATLAB which employs Machine Learning Algorithms and proves that the Least Mean Squared approach (LMS) is the best option for a simple antenna.
This project involves a MATLAB script designed for simulating different adaptive beamforming algorithms.
✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】
The Matlab Simulation codes for Hybrid Beamforming for Millimeter Wave Systems Using the MMSE Criterion.
Matlab files for various types of beamforming
A simple example with how hybrid beamforming is employed at the transmit end of a massive MIMO communications system.
Simulation code for “Massive MIMO and Small Cells: Improving Energy Efficiency by Optimal Soft-Cell Coordination” by Emil Björnson, Marios Kountouris, Mérouane Debbah, Proceedings of International …
wireless network simulation(using OMNet++5.0)
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
Code for Tiny Python Projects (Manning, 2020, ISBN 1617297518). Learning Python through test-driven development of games and puzzles.
A collection of simple python mini projects to enhance your python skills
All Algorithms implemented in Python
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)