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Zhiyuan Ning

24 papers hereh-index 11332 citations31 works total

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

author position
  • first author5
  • middle author18

Across the 23 of 24 papers where every author was matched, so the position is known.

fields
  • cs.LG9
  • cs.CL6
  • cs.AI4
  • cs.IR3
  • cs.CV1
  • q-bio.GN1
same name
  • Zhiyuan Ning — 7 papers, h 2
  • Zhiyuan Ning — 4 papers, h 3
  • Zhiyuan Ning — 2 papers, h 2
  • Zhiyuan Ning — 1 paper
  • Zhiyuan Ning — 1 paper
  • Zhiyuan Ning — 1 paper

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
20202026
most citedRPT: Toward Transferable Model on Heterogeneous Researcher Data via Pre-Training

14 citations · 32 across the 23 of their papers we have counts for

collaborators
Showing 2025 · cs.LGShow all

4 papers · 2 filters

cs.LG2025

Soft Graph Clustering for single-cell RNA Sequencing Data

Ping Xu, Pengfei Wang, Zhiyuan Ning +3

Clustering analysis is fundamental in single-cell RNA sequencing (scRNA-seq) data analysis for elucidating cellular heterogeneity and diversity. Recent graph-based scRNA-seq cluste…

cs.LG2025

Rethinking Graph Contrastive Learning through Relative Similarity Preservation

Zhiyuan Ning, Pengfei Wang, Ziyue Qiao +2

Graph contrastive learning (GCL) has achieved remarkable success by following the computer vision paradigm of preserving absolute similarity between augmented views. However, this…

cs.LG2025

Deep Cut-informed Graph Embedding and Clustering

Zhiyuan Ning, Zaitian Wang, Ran Zhang +8

Graph clustering aims to divide the graph into different clusters. The recently emerging deep graph clustering approaches are largely built on graph neural networks (GNN). However,…

cs.LG2025

Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimization

Xiaohan Huang, Dongjie Wang, Zhiyuan Ning +7

Feature transformation methods aim to find an optimal mathematical feature-feature crossing process that generates high-value features and improves the performance of downstream ma…

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