limeng-1234

limeng-1234's Stars

• wayveai/Driving-with-LLMs

  PyTorch implementation for the paper "Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving"

  Language:Python46741

• autonomousvision/plant

  [CoRL'22] PlanT: Explainable Planning Transformers via Object-Level Representations

  Language:Python23231

• autonomousvision/transfuser

  [PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

  Language:Python1.2k193

• AtsushiSakai/PythonRobotics

  Python sample codes for robotics algorithms.

  Language:Python23.8k6.6k

• ZikangZhou/HiVT

  [CVPR 2022] HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction

  Language:Python655123

• ZikangZhou/QCNet

  [CVPR 2023] Query-Centric Trajectory Prediction

  Language:Python55384

• academicpages/academicpages.github.io

  Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

  Language:JavaScript12.8k44.7k

• wayveai/mile

  PyTorch code for the paper "Model-Based Imitation Learning for Urban Driving".

  Language:Python36834

• OpenDriveLab/UniAD

  [CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving

  Language:Python3.7k415

• kf-liu/The-Art-of-Linear-Algebra-zh-CN

  Graphic notes on Gilbert Strang's "Linear Algebra for Everyone", 线性代数的艺术中文版, 欢迎PR.

  Language:PostScript4.6k454

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook48.3k5.7k

• Jerry00917/samshap

  Code for the paper "Explain Any Concept: Segment Anything Meets Concept-Based Explanation". Poster @ NeurIPS 2023

  Language:Python413

• ZPdesu/SEAN

  SEAN: Image Synthesis with Semantic Region-Adaptive Normalization (CVPR 2020, Oral)

  Language:Python65595

• eriklindernoren/PyTorch-GAN

  PyTorch implementations of Generative Adversarial Networks.

  Language:Python16.6k4.1k

• wangyongjie-ntu/CFAI

  A collection of algorithms of counterfactual explanations.

  Language:Python508

• SeldonIO/alibi

  Algorithms for explaining machine learning models

  Language:Python2.4k252

• valeoai/STEEX

  STEEX: Steering Counterfactual Explanations with Semantics

  Language:Python183

• valeoai/OCTET

  Language:Python172

• Shahin-01/explainable-AI-for-autonomous-driving

  A compendium of explainable AI (XAI)-based studies for autonomous driving

  5

• Twizwei/bddoia_project

  Language:Python2811

• ChenglongChen/pytorch-DRL

  PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

  Language:Python536106

• heleidsn/UAV_Navigation_DRL_AirSim

  This is a new repo used for training UAV navigation (local path planning) policy using DRL methods.

  Language:Python24134

• aldolipani/OwenShap

  Owen Shapley Sampling

  Language:Jupyter Notebook83

• suinleelab/shapley_algorithms

  Language:Jupyter Notebook172

• starry-sky6688/MADDPG

  Pytorch implementation of the MARL algorithm, MADDPG, which correspondings to the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".

  Language:Python55286

• shariqiqbal2810/maddpg-pytorch

  PyTorch Implementation of MADDPG (Lowe et. al. 2017)

  Language:Python582130

• hsvgbkhgbv/SQDDPG

  This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.

  Language:Python11642

• openai/multiagent-particle-envs

  Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

  Language:Python2.4k791

• hsvgbkhgbv/shapley-q-learning

  This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.

  Language:Python4313

• Farama-Foundation/HighwayEnv

  A minimalist environment for decision-making in autonomous driving

  Language:Python2.7k767