yuzhouxianzhi Goto Github PK

advtrajectoryprediction

Implementation of CVPR 2022 paper "On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles" https://arxiv.org/abs/2201.05057

automatic_vehicular_control

[IEEE T-ASE] [IROS 2022] Unified Automatic Control of Vehicular Systems With Reinforcement Learning

automotivedrivingmodels.jl

Driving simulation architecture for Julia

bayesianrlforautonomousdriving

bevheight

An official code release of our CVPR'23 paper, BEVHeight

bilevel-optimization-in-coordination-game

code implementation for 'Bi-level Actor-Critic for Multi-agent Coordination'(AAAI2020)

carla-rl

Reinforcement Learning Agents Trained in the CARLA Simulator

cobevflow

[NeurIPS 2023] Asynchrony-Robust Collaborative Perception via Bird’s Eye View Flow

coiltraine

Training framework for conditional imitation learning

crossing-crowdsourcing

A framework for the analysis of perceived risk in the interaction between pedestrian and vehicle, from the perspective of the driver using a crowdsourcing approach.

decentralized_bottlenecks

Code and figures for bottlenecks paper

decision-transformer

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deeplearning

deepsocial

Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic and Beyond

densetrafficeval

di-drive

OpenDILab Auto-driving platform

domainmix

[BMVC2021] The official implementation of "DomainMix: Learning Generalizable Person Re-Identification Without Human Annotations"

drift_drl

High-speed Autonomous Drifting with Deep Reinforcement Learning

drone-dataset-tools

The goal of this repo is to make the inD dataset as easy to use as possible. For this purpose we provide source code in Python, which allows the import and visualization of the dataset.

dsac

Distributional Soft Actor Critic

dynamic-congestion-prediction

Algorithms for prediction of congestion from Network State

easy-rl

强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/

easyrl

EasyRL

flow

Computational framework for reinforcement learning in traffic control

fost

FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.

gail-pytorch

A simple implementation of Generative Adversarial Imitation Learning with PyTorch

gcn-gan-for-weighted-dynamic-networks

GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks

gnn

gpt4v-ad-exploration

On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving