◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Chao Qu

13 papers hereh-index 429 citations14 works total

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

author position
  • middle author12
  • last author1

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI3
  • physics.chem-ph2
  • cs.CV1
same name
  • Chao Qu — 10 papers, h 10
  • Chao Qu — 8 papers, h 13
  • Chao Qu — 5 papers, h 6
  • Chao Qu — 4 papers, h 2
  • Chao Qu — 1 paper
  • Chao Qu — 1 paper, h 2

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

activity
20242026
most citedEquivariant Spherical Transformer for Efficient Molecular Modeling

1 citations · 2 across the 13 of their papers we have counts for

collaborators
Showing 2025 · cs.LGShow all

4 papers · 2 filters

cs.LG2025

Unleashing Flow Policies with Distributional Critics

Deshu Chen, Yuchen Liu, Zhijian Zhou +2

Flow-based policies have recently emerged as a powerful tool in offline and offline-to-online reinforcement learning, capable of modeling the complex, multimodal behaviors found in…

cs.LG2025

Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation

Zhijian Zhou, Junyi An, Zongkai Liu +5

Generating physically realistic 3D molecular structures remains a core challenge in molecular generative modeling. While diffusion models equipped with equivariant neural networks…

cs.LG2025★ 1 cited

Equivariant Spherical Transformer for Efficient Molecular Modeling

Junyi An, Xinyu Lu, Chao Qu +6

Equivariant Graph Neural Networks (GNNs) have significantly advanced the modeling of 3D molecular structure by leveraging group representations. However, their message passing, hea…

cs.LG2025

Equivariant Masked Position Prediction for Efficient Molecular Representation

Junyi An, Chao Qu, Yun-Fei Shi +4

Graph neural networks (GNNs) have shown considerable promise in computational chemistry. However, the limited availability of molecular data raises concerns regarding GNNs' ability…

◍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.