TzuRen's repositories
AlphaNLHoldem
An unoffical implementation of AlphaHoldem. 1v1 nl-holdem AI.
AORPO
Official pytorch implementation of the paper <Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts>.
AutoGL
An autoML framework & toolkit for machine learning on graphs.
awesome-segmentation-saliency-dataset
A collection of some datasets for segmentation / saliency detection. Welcome to PR...:smile:
DB-Football
A Simple, Distributed and Asynchronous Multi-Agent Reinforcement Learning Framework for Google Research Football AI.
dcs
Digital Combat Simulator Python mission framework
DGNet
Deep Gradient Network for Camouflaged Object Detection
eosim-gui
A Graphical User Interface to the OrbitPy and InstruPy packages.
GaLR
Source code of paper "Remote Sensing Cross-Modal Image-Text Retrieval Based on Global and Local Information"
gamesim
Online Learning on Games -- a Simulator
GNIGAN
Gradient-based Nikaido-Isoda optimization
GSCU
Repo for the Greedy when Sure and Conservative when Uncertain about the Opponents (GSCU)
iris
Transformers are Sample Efficient World Models
mmd
Code for magnetic mirror descent
mmd-dilated
An implementation of the QRE solver magnetic mirror descent with dilated entropy (MMD).
REmoteSEnsingOntology
Remote Sensing Ontology
Satellite-Network-Simulators
This is the repository for the collection of satellite network simulators.
SCSU-KR
随着太空和网络空间军事化趋势加剧，我国太空战略面临着日益严峻的挑战。为保障太空网络安全，目前迫切需要形成对卫星网络空间的态势理解能力。本文首先提出了态势理解需要回答的关键性问题，基于空间态势理解本体和空间态势理解知识图谱，构建推理规则，提出基于知识的卫星网络空间态势理解分析方法，通过对卫星网络空间态势理解知识库进行推理，实现对卫星网络安全多源情报自动关联分析。最后，通过案例评估验证了所提方法的有效性和正确性，为我国天基资产保护辅助决策提供支撑。
shapley-q-learning
This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.
spacemission
Branches in this repostiory include tutorials and sample code for web-based mission visualization.
StARformer
Code for paper StARformer: Transformer with State-Action-Reward Representations.
Swarmalators-under-competitive-time-varying-phase-interactions
This is Fortran code for generating the data of scatter plots of the swarmalators and matlab code for plotting the scatter plots in Fig.2, Fig.4 (a), and Fig.7.