Zhenghao Peng | DeepAI

AI Chat

Featured Co-authors

Dahua Lin
142 publications
Bo Dai
134 publications
Cewu Lu
119 publications
Bolei Zhou
99 publications
Hao Sun
91 publications
Lianwen Jin
69 publications
Li Jiang
48 publications
Meng Fang
42 publications
Yuliang Liu
36 publications
Haibin Wu
23 publications
Chunxiao Liu
18 publications

∙ 06/21/2023

ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling

Large-scale driving datasets such as Waymo Open Dataset and nuScenes sub...

0 Quanyi Li, et al. ∙

∙ 03/03/2023

Guarded Policy Optimization with Imperfect Online Demonstrations

The Teacher-Student Framework (TSF) is a reinforcement learning setting ...

0 Zhenghai Xue, et al. ∙

∙ 10/12/2022

TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios

Diverse and realistic traffic scenarios are crucial for evaluating the A...

0 Lan Feng, et al. ∙

∙ 05/31/2022

Human-AI Shared Control via Frequency-based Policy Dissection

Human-AI shared control allows human to interact and collaborate with AI...

0 Quanyi Li, et al. ∙

∙ 04/05/2022

Action-Conditioned Contrastive Policy Pretraining

Deep visuomotor policy learning achieves promising results in control ta...

2 Qihang Zhang, et al. ∙

∙ 03/19/2022

SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition

End-to-end scene text spotting has attracted great attention in recent y...

0 Mingxin Huang, et al. ∙

∙ 02/17/2022

Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization

Human intervention is an effective way to inject human knowledge into th...

0 Quanyi Li, et al. ∙

∙ 10/26/2021

Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization

Self-Driven Particles (SDP) describe a category of multi-agent systems c...

0 Zhenghao Peng, et al. ∙

∙ 10/13/2021

Safe Driving via Expert Guided Policy Optimization

When learning common skills like driving, beginners usually have domain ...

0 Zhenghao Peng, et al. ∙

∙ 09/26/2021

MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning

Driving safely requires multiple capabilities from human and intelligent...

7 Quanyi Li, et al. ∙

∙ 07/09/2021

Safe Exploration by Solving Early Terminated MDP

Safe exploration is crucial for the real-world application of reinforcem...

0 Hao Sun, et al. ∙

∙ 12/26/2020

Improving the Generalization of End-to-End Driving through Procedural Generation

Recently there is a growing interest in the end-to-end training of auton...

6 Quanyi Li, et al. ∙

∙ 06/14/2020

Non-local Policy Optimization via Diversity-regularized Collaborative Exploration

Conventional Reinforcement Learning (RL) algorithms usually have one sin...

0 Zhenghao Peng, et al. ∙

∙ 05/21/2020

Novel Policy Seeking with Constrained Optimization

In this work, we address the problem of learning to seek novel policies ...

6 Hao Sun, et al. ∙

∙ 07/27/2018

AXNet: ApproXimate computing using an end-to-end trainable neural network

Neural network based approximate computing is a universal architecture p...

0 Zhenghao Peng, et al. ∙

∙ 05/23/2018

Approximate Random Dropout

The training phases of Deep neural network (DNN) consume enormous proces...

0 Zhuoran Song, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world