◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Hao Su

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.RO1
  • quant-ph1
ORCID 0000-0002-0178-6610
same name
  • Hao Su — 31 papers
  • Hao Su — 14 papers, h 40
  • Hao Su — 14 papers
  • Hao Su — 7 papers
  • Hao Su — 6 papers
  • Hao Su — 4 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSolving Graph Problems Using Gaussian Boson Sampling

58 citations · 70 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2023★ 6 cited

On the Efficacy of 3D Point Cloud Reinforcement Learning

Zhan Ling, Yunchao Yao, Xuanlin Li +1

Recent studies on visual reinforcement learning (visual RL) have explored the use of 3D visual representations. However, none of these work has systematically compared the efficacy…

cs.LG2023★ 1 cited

Boosting Reinforcement Learning and Planning with Demonstrations: A Survey

Tongzhou Mu, Hao Su

Although reinforcement learning has seen tremendous success recently, this kind of trial-and-error learning can be impractical or inefficient in complex environments. The use of de…

quant-ph2023★ 58 cited

Solving Graph Problems Using Gaussian Boson Sampling

Yu-Hao Deng, Si-Qiu Gong, Yi-Chao Gu +21

Gaussian boson sampling (GBS) is not only a feasible protocol for demonstrating quantum computational advantage, but also mathematically associated with certain graph-related and q…

cs.LG2022★ 5 cited

Improving Policy Optimization with Generalist-Specialist Learning

Zhiwei Jia, Xuanlin Li, Zhan Ling +3

Generalization in deep reinforcement learning over unseen environment variations usually requires policy learning over a large set of diverse training variations. We empirically ob…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.