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Topics: Generative Models & Optimal Transport / Stochastic Control & Sampling / Equivariant Neural Networks / Large Language Models / Molecular Discovery / AI for Science (* denotes equal contribution, † denotes advising role)

FEAT: Free energy Estimators with Adaptive Transport
Yuanqi Du*, Jiajun He*, Francisco Vargas, ..., Eric Vanden-Eijnden
NeurIPS 2025 | paper

RNE: A Plug-and-play Framework for Diffusion Density Estimation and Inference-time Control
Jiajun He, José Miguel Hernández-Lobato, Yuanqi Du†, Francisco Vargas†
arXiv preprint arXiv:2506.05668 | paper

Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference
Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann
NeurIPS 2025 (Spotlight) | paper

CREPE: Controlling Diffusion with Replica Exchange
Jiajun He, ..., Yuanqi Du, Saifuddin Syed, Francisco Vargas
arXiv preprint arXiv:2509.23265 | paper

Accelerated Parallel Tempering via Neural Transports
Leo Zhang, Peter Potaptchik, Jiajun He, Yuanqi Du, et al, Saifuddin Syed
arXiv preprint arXiv:2502.10328 | paper

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers
Jiajun He*, Yuanqi Du*, Francisco Vargas, ..., Carla P. Gomes, José Miguel Hernández-Lobato
arXiv preprint arXiv:2502.06685 | paper

LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du†, Chao Zhang†
ICML 2025 | paper

Efficient Evolutionary Search over Chemical Space with Large Language Models
Haorui Wang*, Marta Skreta*, …, Yuanqi Du†, Alán Aspuru-Guzik†, Kirill Neklyudov†, Chao Zhang†
ICLR 2025 | paper

Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge and Reasoning Capability of Large Language Models
Jieyu Lu, Zhangde Song, Qiyuan Zhao, Yuanqi Du, Yirui Cao, Haojun Jia, Chenru Duan
JACS 2025 (Cover Article) | paper

Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
Yuanqi Du*, Lingkai Kong*, Wenhao Mu*, Kirill Neklyudov, Valentin De Bortol, ..., Yi-An Ma, Carla P. Gomes, Chao Zhang
AISTATS 2025 | paper

React-OT: Optimal Transport for Generating Transition State in Chemical Reactions
Chenru Duan*, Guan-Horng Liu*, Yuanqi Du*, ..., Carla P. Gomes, Evangelos A. Theodorou, Heather J. Kulik
Nature Machine Intelligence 2025 (Cover Article) | paper

Large Language Models Are Innate Crystal Structure Generators
Jingru Gan, Peichen Zhong*, Yuanqi Du*, ..., Carla P. Gomes, Kristin A. Persson, Daniel Schwalbe-Koda, Wei Wang
arXiv preprint | paper

AlphaNet: Scaling Up Local Frame-based Atomistic Foundation Model
Bangchen Yin, Jiaao Wang†, …, Yuanqi Du†, Carla P. Gomes, Chenru Duan†, Hai Xiao†, Graeme Henkelman†
npj Computational Materials 2025 | paper

Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
Yuanqi Du*, Michael Plainer*, Rob Brekelmans*, ..., Carla P. Gomes, Alán Aspuru-Guzik, Kirill Neklyudov
NeurIPS 2024 (Spotlight) | paper

Navigating Chemical Space with Latent Flows
Guanghao Wei*, Yining Huang*, Chenru Duan, Yue Song†, Yuanqi Du†
NeurIPS 2024 | paper

Machine Learning-Aided Generative Molecular Design
Yuanqi Du*, Arian R. Jamasb*, Jeff Guo*, ..., Pietro Lio, Philippe Schwaller, Tom L. Blundell
Nature Machine Intelligence 2024 | paper

Structure-based Drug Design with Equivariant Diffusion Models
Arne Schneuing*, Charles Harris*, Yuanqi Du*, ..., Carla P. Gomes, Tom Blundell, Pietro Lió, Max Welling, Michael Bronstein, Bruno Correia
Nature Computational Science 2024 | paper

Molecular Contrastive Pretraining with Collaborative Featurizations
Yanqiao Zhu*, Dingshuo Chen*, Yuanqi Du*, Yingze Wang, Qiang Liu, Shu Wu
NeurIPS 2024 | paper

Aligning Large Language Models with Representation Editing: A Control Perspective
Lingkai Kong, Haorui Wang, Wenhao Mu, Yuanqi Du, ..., Chao Zhang
NeurIPS 2024 | paper

Large Language Models are Catalyzing Chemistry Education
Yuanqi Du*, Chenru Duan*, Andres Bran*, ..., Heather Kulik, Antoine Bosselut, Jinjia Xu, Philippe Schwaller
ChemRxiv 10.26434/chemrxiv-2024-h722v | paper

Accurate Transition State Generation with an Object-aware Equivariant Elementary Reaction Diffusion Model
Chenru Duan, Yuanqi Du, Haojun Jia, Heather J. Kulik
Nature Computational Science 2023 (Cover Article) | paper

Scientific Discovery in the Age of Artificial Intelligence
Hanchen Wang*, Tianfan Fu*, Yuanqi Du*, ..., Max Welling, Linfeng Zhang, Connor Coley, Yoshua Bengio, Marinka Zitnik
Nature 2023 | paper

A New Perspective on Building Efficient and Expressive 3D Equivariant Graph Neural Networks
Weitao Du*, Yuanqi Du*, Limei Wang*, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma
NeurIPS 2023 | paper

Path Integral Stochastic Optimal Control for Sampling Transition Paths
Lars Holdijk*, Yuanqi Du*, Priyank Jaini, Ferry Hooft, Bernd Ensing, Max Welling
NeurIPS 2023 | paper

M²Hub: Unlocking the Potential of Machine Learning for Materials Discovery
Yuanqi Du*, Yingheng Wang*, Yining Huang, ..., Tian Xie, Chenru Duan, John M. Gregoire, Carla P. Gomes
NeurIPS 2023 | paper

Uncovering Neural Scaling Law in Molecular Representation Learning
Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang
NeurIPS 2023 | paper

A Flexible Diffusion Model
Weitao Du, Tao Yang, He Zhang, Yuanqi Du
ICML 2023 | paper

ChemSpacE: Interpretable and Interactive Chemical Space Exploration
Yuanqi Du, Xian Liu, Shengchao Liu, Jieyu Zhang, Bolei Zhou
TMLR 2023 | paper

A Systematic Survey of Chemical Pre-trained Models
Jun Xia*, Yanqiao Zhu*, Yuanqi Du*, Stan Z.Li
IJCAI 2023 | paper

Artificial intelligence for science in quantum, atomistic, and continuum systems
Xuan Zhang, Limei Wang, ..., Yuanqi Du, ..., Shuiwang Ji
arXiv preprint arXiv:2307.08423 | paper

A Survey on Deep Graph Generation: Methods and Applications
Yuanqi Du*, Yanqiao Zhu*, Yinkai Wang*, Jieyu Zhang, Qiang Liu, Shu Wu
LoG 2022 | paper

Equivariant Graph Neural Networks with Complete Local Frames
Weitao Du*, He Zhang*, Yuanqi Du, Qi Meng, Wei Chen, Tie-Yan Liu, Nanning Zheng, Bin Shao
ICML 2022 | paper

Disentangled Spatiotemporal Graph Generative Models
Yuanqi Du*, Xiaojie Guo*, Hengning Cao, Yanfang Ye, Liang Zhao
AAAI 2022 (Oral) | paper

GraphGT: Machine Learning Datasets for Graph Generation and Transformation
Yuanqi Du*, Shiyu Wang*, Xiaojie Guo, ..., Liang Zhao
NeurIPS 2021 | paper

Deep Generative Model for Spatial Networks
Xiaojie Guo*, Yuanqi Du*, Liang Zhao.
KDD 2021 | paper