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researcher

Yusong Wang

13 papers hereh-index 12558 citations26 works total

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

author position
  • first author3
  • middle author9

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • physics.chem-ph2
  • q-bio.QM2
  • cs.AI1
  • cs.CL1
  • q-bio.BM1
same name
  • Yusong Wang — 14 papers, h 8
  • Yusong Wang — 3 papers, h 1
  • Yusong Wang — 2 papers, h 4
  • Yusong Wang — 2 papers, h 27
  • Yusong Wang — 2 papers, h 1
  • Yusong Wang — 1 paper, h 1

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
20212026
most citedDirect Molecular Conformation Generation

24 citations · 51 across the 12 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

Tokenizing 3D Molecule Structure with Quantized Spherical Coordinates

Kaiyuan Gao, Yusong Wang, Haoxiang Guan +5

The application of language models (LMs) to molecular structure generation using line notations such as SMILES and SELFIES has been well-established in the field of cheminformatics…

cs.LG2024

Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs

Yusong Wang, Chaoran Cheng, Shaoning Li +5

Geometric graph neural networks (GNNs) have emerged as powerful tools for modeling molecular geometry. However, they encounter limitations in effectively capturing long-range inter…

cs.LG2024★ 5 cited

Improving AlphaFlow for Efficient Protein Ensembles Generation

Shaoning Li, Mingyu Li, Yusong Wang +4

Investigating conformational landscapes of proteins is a crucial way to understand their biological functions and properties. AlphaFlow stands out as a sequence-conditioned generat…

q-bio.QM2024★ 2 cited

F3low: Frame-to-Frame Coarse-grained Molecular Dynamics with SE(3) Guided Flow Matching

Shaoning Li, Yusong Wang, Mingyu Li +4

Molecular dynamics (MD) is a crucial technique for simulating biological systems, enabling the exploration of their dynamic nature and fostering an understanding of their functions…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.