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ZhouHang's Projects

autoformer icon autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

dgl icon dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dmsc-visualizer icon dmsc-visualizer

A library to visualize (keplerian) orbital movements of a satellite network in 3D using OpenGL® 4.2.

flowformer icon flowformer

About Code release for "Flowformer: Linearizing Transformers with Conservation Flows" (ICML 2022), https://arxiv.org/pdf/2202.06258.pdf

gdn icon gdn

Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series"

gta icon gta

Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT

informer icon informer

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

lleoscn-cdn-sim icon lleoscn-cdn-sim

Simulation tool for CDN replication in large low-earth orbit satellite access networks.

merlion icon merlion

Merlion: A Machine Learning Framework for Time Series Intelligence

mrta icon mrta

Multi-agent task allocation

mtad-gat-pytorch icon mtad-gat-pytorch

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

ns3-ai icon ns3-ai

Enable the interaction between ns-3 and popular frameworks using Python, which mean you can train and test your AI algorithms in ns-3 without changing any frameworks you are using now!

ns3-mmwave icon ns3-mmwave

ns-3 module for simulating mmWave-based cellular systems. See https://ieeexplore.ieee.org/document/8344116/ (open access) as a reference.

nsibf icon nsibf

Code for KDD' 21 paper: Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering

off-policy icon off-policy

PyTorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.

on-policy icon on-policy

This is the official implementation of Multi-Agent PPO (MAPPO).

optimization-for-leo-satellites-network icon optimization-for-leo-satellites-network

The current generation of LEO constellations assumes that each LEO satellite covers a ground area regardless of the number of end users or terminals operating in the same area. The satellite solution to the communication problem, both in terms of reach and quality, is lacking when we talk about optimization in QoS aspects. (latency and throughput The questions our project deals with are What are the requirements for the QoS? What QoS can we provide with efficient routing in the given constellation? How to maximize the number of users for a specific region and QoS? How many satellites will suffice for the desired QoS in the given constellation? In addition to the geographical difficulties of routing, there is a delay time problem and therefore the processing time of the routing algorithm has a great impact. The problem the project will deal with is traffic routing for a satellite network based on LEO satellites, considering various service metrics.

positionbasedoncommunicationsatellite icon positionbasedoncommunicationsatellite

This software has developed a positioning software based on the Iridium satellite signal based on the C/C++ language and windows + QT platform, which basically realizes the following functions: 1. Doppler information processing and extraction and image presentation after the hardware collects the input data; 2. TLE update tool mainly for Iridium; 3. Automatic identification, overhead satellite prediction and positioning based on the extracted Doppler information and the satellite number of the TLE file, and displayed on the graphical interface based on Baidu Map API;

qt-cesium icon qt-cesium

QtJSBSim modular flight simulator, front end for JSBSim

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