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Yuanqi Du

12 papers hereh-index 7106 citations15 works total

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

author position
  • middle author8
  • last author4

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

fields
  • cs.LG4
  • stat.ML4
  • cond-mat.mtrl-sci2
  • cond-mat.stat-mech1
  • cs.CL1
same name
  • Yuanqi Du — 20 papers, h 24
  • Yuanqi Du — 10 papers, h 8
  • Yuanqi Du — 6 papers, h 4
  • Yuanqi Du — 5 papers, h 2
  • Yuanqi Du — 2 papers
  • Yuanqi Du — 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

most citedNo Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers

2 citations · 2 across the 10 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2026

Free energy Estimation on Any State Space

Jiajun He, Zijing Ou, Francisco Vargas +4

Free energy estimation is a fundamental yet challenging problem, from physics to statistics. Classical approaches rely on thermodynamic transformations, ranging from direct estimat…

stat.ML2026

A unified perspective on fine-tuning and sampling with diffusion and flow models

Carles Domingo-Enrich, Yuanqi Du, Michael S. Albergo

We study the problem of training diffusion and flow generative models to sample from target distributions defined by an exponential tilting of a base density; a formulation that su…

stat.ML2025

FEAT: Free energy Estimators with Adaptive Transport

Jiajun He, Yuanqi Du, Francisco Vargas +4

We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation -- a critical challenge across scientific domains. FEAT leverages lea…

stat.ML2025

Accelerated Parallel Tempering via Neural Transports

Leo Zhang, Peter Potaptchik, Jiajun He +5

Markov Chain Monte Carlo (MCMC) algorithms are essential tools in computational statistics for sampling from unnormalised probability distributions, but can be fragile when targeti…

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