Viet-Hoang Tran

I'm currently a fourth-year Ph.D. student in the Department of Mathematics, National University of Singapore.

I began my Ph.D. in August 2022 in Mathematics. In September 2023, I shifted my research focus to Machine Learning and started working under the supervision of Professor Tan Minh Nguyen.

Previously, I completed an Honors degree in Mathematics at the Hanoi University of Science (2018-2022).

email: hoang.tranviet [at] u.nus.edu | Google Scholar

Research Interests

• My research focuses on symmetries in neural networks: understanding how distinct parameter configurations can represent the same function and characterizing the relationships between them. I am also interested in applications of these symmetries, including equivariant metanetworks, neural conservation laws, linear mode connectivity up to symmetry, and model merging.

• I am also interested in AI-assisted mathematical reasoning and theorem proving, and, more broadly, in understanding the reasoning capabilities and limitations of LLMs.

keywords: machine learning, parameter space symmetry, mode connectivity, neural conservation law, metanetwork

News

• Aug 2026. Amid the Math-AI hype, with help from GPT-5.6 Sol and Fable, we solved Bayart's formal power-series problem: If R is Noetherian and R[[x]] is a UFD, then so is R[[x,y]]. Preprint available here.

• May 2026. 3 papers accepted at ICML 2026:

  • Conservation Laws for Modern Neural Architectures (spotlight)

  • Functional Equivalence in Attention: A Comprehensive Study with Applications to Linear Mode Connectivity

  • Geometric and Stochastic Analysis of Discontinuities in Sparse Mixture-of-Experts (spotlight)

• Jan 2026. 4 papers accepted at ICLR 2026:

  • Quasi-Equivariant Metanetworks

  • Mixed-Curvature Tree-Sliced Wasserstein Distance

  • Tree-sliced Sobolev IPM

  • Revisiting Tree-Sliced Wasserstein Distance Through the Lens of the Fermat-Weber Problem

Selected Publications

• Conservation Laws for Modern Neural Architectures
  Viet-Hoang Tran¹, Vinh Khanh Bui¹, Tan Lai Ngoc, Nam Nguyen, Tuan Dam, Tan M. Nguyen²
  ICML 2026 (spotlight)

• On Linear Mode Connectivity of Mixture-of-Experts Architectures
  Viet-Hoang Tran¹, Van Hoan Trinh¹, Khanh Vinh Bui¹, Tan M. Nguyen²
  NeurIPS 2025 (oral)

• Equivariant Neural Functional Networks for Transformers
  Viet-Hoang Tran¹, Thieu N. Vo¹, An Nguyen The¹, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen²
  ICLR 2025
  

• Distance-Based Tree-Sliced Wasserstein Distance
  Viet-Hoang Tran¹, Khoi N.M. Nguyen¹, Trang Pham, Thanh T. Chu, Tam Le², Tan M. Nguyen²
  ICLR 2025
  

> all publications