Mingtzge's Stars
satwikkansal/wtfpython
What the f*ck Python? 😱
openai/gym
A toolkit for developing and comparing reinforcement learning algorithms.
nndl/nndl.github.io
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
Unity-Technologies/ml-agents
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
openai/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
leisurelicht/wtfpython-cn
wtfpython的中文翻译/施工结束/ 能力有限，欢迎帮我改进翻译
openai/spinningup
An educational resource to help anyone learn deep reinforcement learning.
shenweichen/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
STVIR/pysot
SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
ikostrikov/pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
wzhe06/SparrowRecSys
A Deep Learning Recommender System
zju3dv/LoFTR
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022
LyWangPX/Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
Solutions of Reinforcement Learning, An Introduction
hila-chefer/Transformer-Explainability
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
sfujim/TD3
Author's PyTorch implementation of TD3 for OpenAI gym tasks
openai/maddpg
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Tencent/FeatherCNN
FeatherCNN is a high performance inference engine for convolutional neural networks.
huawei-noah/SMARTS
Scalable Multi-Agent RL Training School for Autonomous Driving
zhangchuheng123/Reinforcement-Implementation
Implementation of benchmark RL algorithms
StrangerZhang/pysot-toolkit
Python Single Object Tracking Evaluation
RunzheYang/MORL
Multi-Objective Reinforcement Learning
kniost/BUPT-Resources
北邮研究生毕业论文模板以及各种校内信息
KernelErr/realtime-object-detector
Flutter real-time object detection App with Paddle-Lite and YOLO v3.
aim-uofa/RGM
uber-research/MARVIN
Uber's Multi-Agent Routing Value Iteration Network
cardwing/Codes-for-RL-PER
A novel DDPG method with prioritized experience replay (IEEE SMC 2017)
huipengly/MFAC
Model Free Adaptive Control
Mingtzge/PVE-MCC_for_unsignalized_intersection
Aiming at the problem of the traffic efficiency of intelligent networked vehicles passing through unsignalized-intersection in the future smart cities, this project proposed a Progressive Value-expectation Estimation Multi-agent Cooperative Control (PVE-MCC) algorithm based on reinforcement learning. The algorithm takes the intelligent networked vehicles as the research object and designed the reward function for the optimization objective from the three aspects of traffic efficiency, safety, and comfort.
Mingtzge/MiVeCC_with_DRL
This is a Multi-intersection Vehicular Cooperative Control (MiVeCC) scheme to enable cooperation among vehicles in a 3*3 unsignalized intersections. we proposed a algorithm combined heuristic-rule and two-stage deep reinforcement learning. The heuristic-rule achieves vehicles across the intersections without collisions. Based on the heuristic-rule, DDPG is used to optimize the collaborative control of vehicles and improve the traffic efficiency. Simulation results show that the proposed algorithm can improve travel efficiency at multiple intersections by up to 4.59 times without collision compared with existing methods.
tasx0823/tasx0823.github.io
Sun Xiao