Haolin Ye
Scholar

Haolin Ye

Google Scholar ID: vFImvb8AAAAJ
Bachelor Student of Computer Science and Mathematics, McGill University
machine learning
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
9
 
H-index
2
 
i10-index
0
 
Publications
7
 
Co-authors
1
list available
Contact
Emailhaolin.ye@mail.mcgill.caCVOpen ↗GitHubOpen ↗LinkedInOpen ↗
Publications
5 items
Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
2026
Cited
0
Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generation with Hard Constraints
2026
Cited
0
Extracting Interpretable Logic Rules from Graph Neural Networks
2025
Cited
0
Learning Interpretable Logic Rules from Deep Vision Models
2025
Cited
0
Learning Minimal Neural Specifications
2024
Cited
0
Resume (English only)
Research Experience
  • Worked as a student researcher at Mila AI Institute from May 1, 2022 to January 1, 2023.
Education
  • Third year undergraduate student at McGill University.
Background
  • Research interests: formal methods, machine learning theory; Fields: geometry, mathematical optimization.
Co-authors
1 total
Brigitte Pientka
Brigitte Pientka
McGill University