American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract). - Yuanqi Du; Nguyen Dang 002; Riley Wilkerson; Parth H. Pathak; Huzefa Rangwala; Jana Kosecka (AAAI, 2020)

Expressive ASL Recognition using Millimeter-wave Wireless Signals. - Panneer Selvam Santhalingam; Yuanqi Du; Riley Wilkerson; Al Amin Hosain; Ding Zhang; Parth H. Pathak; Huzefa Rangwala; Raja S. Kushalnagar (SECON, 2020)

CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models. - Quan Quan; Qiyuan Wang 001; Liu Li; Yuanqi Du; S. Kevin Zhou (CoRR, 2020)

Deep Latent-Variable Models for Controllable Molecule Generation. - Yuanqi Du; Yinkai Wang; Fardina Fathmiul Alam; Yuanjie Lu; Xiaojie Guo 002; Liang Zhao 002; Amarda Shehu (BIBM, 2021)

Ensemble Machine Learning System for Student AcademicPerformance Prediction. - Yinkai Wang; Aowei Ding; Kaiyi Guan; Yuanqi Du (EDM (Workshops), 2021)

Graph Representation Learning for Protein Conformation Sampling. - Taseef Rahman; Yuanqi Du; Amarda Shehu (ICCABS, 2021)

Property Controllable Variational Autoencoder via Invertible Mutual Dependence. - Xiaojie Guo 002; Yuanqi Du; Liang Zhao 002 (ICLR, 2021)

Deep Generative Models for Spatial Networks. - Xiaojie Guo 002; Yuanqi Du; Liang Zhao 002 (KDD, 2021)

GraphGT: Machine Learning Datasets for Graph Generation and Transformation. - Yuanqi Du; Shiyu Wang 002; Xiaojie Guo 002; Hengning Cao; Shujie Hu; Junji Jiang; Aishwarya Varala; Abhinav Angirekula; Liang Zhao 002 (NeurIPS Datasets and Benchmarks, 2021)

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models. - Pengbo Liu 004; Hu Han 001; Yuanqi Du; Heqin Zhu; Yinhao Li; Feng Gu; Honghu Xiao; Jun Li 103; Chunpeng Zhao; Li Xiao 005; Xinbao Wu; S. Kevin Zhou (Int. J. Comput. Assist. Radiol. Surg., 2021)

Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image. - Yuanqi Du; Quan Quan; Hu Han 001; S. Kevin Zhou (CoRR, 2021)

Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning. - Ziming Liu; Yunyue Chen; Yuanqi Du; Max Tegmark (CoRR, 2021)

Equivariant vector field network for many-body system modeling. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Bin Shao; Tie-Yan Liu (CoRR, 2021)

Graph-based Ensemble Machine Learning for Student Performance Prediction. - Yinkai Wang; Aowei Ding; Kaiyi Guan; Shixi Wu; Yuanqi Du (CoRR, 2021)

Dataset for Generative Adversarial Learning of Protein Tertiary Structures. Molecules, 2021. - Taseef Rahman; Yuanqi Du; Liang Zhao 002; Amarda Shehu (IEEE DataPort, 2021)

Dataset for Disentangled Representation Learning for Interpretable Molecule Generation. - Yuanqi Du; Xiaojie Guo 002; Amarda Shehu; Liang Zhao 002 (IEEE DataPort, 2021)

Disentangled Spatiotemporal Graph Generative Models. - Yuanqi Du; Xiaojie Guo 002; Hengning Cao; Yanfang Ye 001; Liang Zhao 002 (AAAI, 2022)

Property-Controllable Generation of Quaternary Ammonium Compounds. - Bo Pan; Yinkai Wang; Xuanyang Lin; Muran Qin; Yuanqi Du; Shiva Ghaemi; Aowei Ding; Shiyu Wang 002; Saleh AlKhalifa; Kevin Minbiole; William M. Wuest; Ashley Ann Petersen; et al. (BIBM, 2022)

SE(3) Equivariant Graph Neural Networks with Complete Local Frames. - Weitao Du; He Zhang; Yuanqi Du; Qi Meng; Wei Chen 034; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (ICML, 2022)

Semi-Supervised Pseudo-Healthy Image Synthesis via Confidence Augmentation. - Yuanqi Du; Quan Quan; Hu Han 001; S. Kevin Zhou (ISBI, 2022)

A Survey on Deep Graph Generation: Methods and Applications. - Yanqiao Zhu 001; Yuanqi Du; Yinkai Wang; Yichen Xu; Jieyu Zhang 001; Qiang Liu 006; Shu Wu (LoG, 2022)

The First Learning on Graphs Conference: Preface. - Bastian Rieck; Razvan Pascanu; Yuanqi Du; Hannes Stärk; Derek Lim; Chaitanya K. Joshi; Andreea Deac; Iulia Duta; Joshua Robinson 001; Gabriele Corso; Leonardo Cotta; Yanqiao Zhu 001; et al. (LoG, 2022)

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks. - Arian R. Jamasb; Ramón Viñas Torné 001; Eric Ma; Yuanqi Du; Charles Harris; Kexin Huang; Dominic Hall; Pietro Lió; Tom L. Blundell (NeurIPS, 2022)

Audio-Driven Co-Speech Gesture Video Generation. - Xian Liu; Qianyi Wu; Hang Zhou 009; Yuanqi Du; Wayne Wu; Dahua Lin; Ziwei Liu 002 (NeurIPS, 2022)

Multi-objective Deep Data Generation with Correlated Property Control. - Shiyu Wang 002; Xiaojie Guo 002; Xuanyang Lin; Bo Pan; Yuanqi Du; Yinkai Wang; Yanfang Ye 001; Ashley Ann Petersen; Austin Leitgeb; Saleh AlKhalifa; Kevin Minbiole; William M. Wuest; et al. (NeurIPS, 2022)

Interpretable Molecular Graph Generation via Monotonic Constraints. - Yuanqi Du; Xiaojie Guo 002; Amarda Shehu; Liang Zhao 002 (SDM, 2022)

Small molecule generation via disentangled representation learning. - Yuanqi Du; Xiaojie Guo 002; Yinkai Wang; Amarda Shehu; Liang Zhao 002 (Bioinform., 2022)

A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications. - Jun Xia 001; Yanqiao Zhu 001; Yuanqi Du; Stan Z. Li (CoRR, 2022)

Recovering medical images from CT film photos. - Quan Quan; Qiyuan Wang 001; Yuanqi Du; Liu Li; S. Kevin Zhou (CoRR, 2022)

MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. - Yuanqi Du; Tianfan Fu; Jimeng Sun 001; Shengchao Liu (CoRR, 2022)

Path Integral Stochastic Optimal Control for Sampling Transition Paths. - Lars Holdijk; Yuanqi Du; Ferry Hooft; Priyank Jaini; Bernd Ensing; Max Welling (CoRR, 2022)

Controllable Data Generation by Deep Learning: A Review. - Shiyu Wang 002; Yuanqi Du; Xiaojie Guo 002; Bo Pan; Liang Zhao 002 (CoRR, 2022)

Improving Molecular Pretraining with Complementary Featurizations. - Yanqiao Zhu 001; Dingshuo Chen; Yuanqi Du; Yingze Wang; Qiang Liu 006; Shu Wu (CoRR, 2022)

Structure-based Drug Design with Equivariant Diffusion Models. - Arne Schneuing; Yuanqi Du; Charles Harris; Arian R. Jamasb; Ilia Igashov; Weitao Du; Tom L. Blundell; Pietro Lió; Carla Gomes 001; Max Welling; Michael M. Bronstein; Bruno E. Correia (CoRR, 2022)

A Systematic Survey of Molecular Pre-trained Models. - Jun Xia 001; Yanqiao Zhu 001; Yuanqi Du; Yue Liu 008; Stan Z. Li (CoRR, 2022)

GAUCHE: A Library for Gaussian Processes in Chemistry. - Ryan-Rhys Griffiths; Leo Klarner; Henry B. Moss; Aditya Ravuri; Sang Truong; Bojana Rankovic; Yuanqi Du; Arian R. Jamasb; Julius Schwartz; Austin Tripp; Gregory Kell; Anthony Bourached; et al. (CoRR, 2022)

Weighted Sampling without Replacement for Deep Top-k Classification. - Dieqiao Feng; Yuanqi Du; Carla P. Gomes; Bart Selman (ICML, 2023)

A Flexible Diffusion Model. - Weitao Du; He Zhang; Tao Yang; Yuanqi Du (ICML, 2023)

A Systematic Survey of Chemical Pre-trained Models. - Jun Xia 001; Yanqiao Zhu 001; Yuanqi Du; Stan Z. Li (IJCAI, 2023)

The Second Learning on Graphs Conference: Preface. - Soledad Villar; Benjamin Paul Chamberlain; Yuanqi Du; Hannes Stärk; Chaitanya K. Joshi; Andreea Deac; Iulia Duta; Joshua Robinson 001; Yanqiao Zhu 001; Kexin Huang; Michelle M. Li; Sofia Bourhim; et al. (LoG, 2023)

Uncovering Neural Scaling Laws in Molecular Representation Learning. - Dingshuo Chen; Yanqiao Zhu 001; Jieyu Zhang 001; Yuanqi Du; Zhixun Li; Qiang Liu 006; Shu Wu; Liang Wang 056 (NeurIPS, 2023)

On Separate Normalization in Self-supervised Transformers. - Xiaohui Chen; Yinkai Wang; Yuanqi Du; Soha Hassoun; Liping Liu 001 (NeurIPS, 2023)

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)

M2Hub: Unlocking the Potential of Machine Learning for Materials Discovery. - Yuanqi Du; Yingheng Wang; Yining Huang; Jianan Canal Li; Yanqiao Zhu 001; Tian Xie; Chenru Duan; John M. Gregoire; Carla Pedro Gomes (NeurIPS, 2023)

GAUCHE: A Library for Gaussian Processes in Chemistry. - Ryan-Rhys Griffiths; Leo Klarner; Henry B. Moss; Aditya Ravuri; Sang Truong; Yuanqi Du; Samuel Stanton; Gary Tom; Bojana Rankovic; Arian Rokkum Jamasb; Aryan Deshwal; Julius Schwartz; et al. (NeurIPS, 2023)

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths. - Lars Holdijk; Yuanqi Du; Ferry Hooft; Priyank Jaini; Bernd Ensing; Max Welling (NeurIPS, 2023)

Pik-Fix: Restoring and Colorizing Old Photos. - Runsheng Xu; Zhengzhong Tu; Yuanqi Du; Xiaoyu Dong; Jinlong Li; Zibo Meng; Jiaqi Ma 003; Alan C. Bovik; Hongkai Yu (WACV, 2023)

Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction. - Junwen Bai; Yuanqi Du; Yingheng Wang; Shufeng Kong; John M. Gregoire; Carla Gomes 001 (CoRR, 2023)

MUBen: Benchmarking the Uncertainty of Pre-Trained Models for Molecular Property Prediction. - Yinghao Li; Lingkai Kong; Yuanqi Du; Yue Yu 001; Yuchen Zhuang; Wenhao Mu; Chao Zhang 014 (CoRR, 2023)

Uncovering Neural Scaling Laws in Molecular Representation Learning. - Dingshuo Chen; Yanqiao Zhu 001; Jieyu Zhang 001; Yuanqi Du; Zhixun Li; Qiang Liu 006; Shu Wu; Liang Wang 001 (CoRR, 2023)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. - Chenru Duan; Yuanqi Du; Haojun Jia; Heather J. Kulik (Nat. Comput. Sci., 2023)

ChemSpacE: Interpretable and Interactive Chemical Space Exploration. - Yuanqi Du; Xian Liu; Nilay Mahesh Shah; Shengchao Liu; Jieyu Zhang; Bolei Zhou (Trans. Mach. Learn. Res., 2023)

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. - Yanqiao Zhu 001; Jeehyun Hwang; Keir Adams; Zhen Liu; Bozhao Nan; Brock Stenfors; Yuanqi Du; Jatin Chauhan; Olaf Wiest; Olexandr Isayev; Connor W. Coley; Yizhou Sun; et al. (ICLR, 2024)

Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling. - Yuanqi Du; Michael Plainer; Rob Brekelmans; Chenru Duan; Frank Noé; Carla P. Gomes; Alán Aspuru-Guzik; Kirill Neklyudov (NeurIPS, 2024)

Aligning Large Language Models with Representation Editing: A Control Perspective. - Lingkai Kong; Haorui Wang; Wenhao Mu; Yuanqi Du; Yuchen Zhuang; Yifei Zhou; Yue Song; Rongzhi Zhang; Kai Wang; Chao Zhang 014 (NeurIPS, 2024)

Navigating Chemical Space with Latent Flows. - Guanghao Wei; Yining Huang; Chenru Duan; Yue Song; Yuanqi Du (NeurIPS, 2024)

React-OT: Optimal Transport for Generating Transition State in Chemical Reactions. - Chenru Duan; Guan-Horng Liu; Yuanqi Du; Tianrong Chen; Qiyuan Zhao; Haojun Jia; Carla P. Gomes; Evangelos A. Theodorou; Heather J. Kulik (CoRR, 2024)

Efficient Evolutionary Search Over Chemical Space with Large Language Models. - Haorui Wang; Marta Skreta; Cher Tian Ser; Wenhao Gao 001; Lingkai Kong; Felix Streith-Kalthoff; Chenru Duan; Yuchen Zhuang; Yue Yu 001; Yanqiao Zhu 001; Yuanqi Du; Alán Aspuru-Guzik; et al. (CoRR, 2024)

Generalized Flow Matching for Transition Dynamics Modeling. - Haibo Wang; Yuxuan Qiu; Yanze Wang; Rob Brekelmans; Yuanqi Du (CoRR, 2024)

Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge of Large Language Models. - Jieyu Lu; Zhangde Song; Qiyuan Zhao; Yuanqi Du; Yirui Cao; Haojun Jia; Chenru Duan (CoRR, 2024)

Machine learning-aided generative molecular design. - Yuanqi Du; Arian R. Jamasb; Jeff Guo; Tianfan Fu; Charles Harris; Yingheng Wang; Chenru Duan; Pietro Liò; Philippe Schwaller; Tom L. Blundell (Nat. Mac. Intell., 2024)

MUBen: Benchmarking the Uncertainty of Molecular Representation Models. - Yinghao Li; Lingkai Kong; Yuanqi Du; Yue Yu 001; Yuchen Zhuang; Wenhao Mu; Chao Zhang 014 (Trans. Mach. Learn. Res., 2024)

Molecular Contrastive Pretraining with Collaborative Featurizations. - Yanqiao Zhu 001; Dingshuo Chen; Yuanqi Du; Yingze Wang; Qiang Liu 006; Shu Wu (J. Chem. Inf. Model., 2024)

Controllable Data Generation by Deep Learning: A Review. - Shiyu Wang 002; Yuanqi Du; Xiaojie Guo 002; Bo Pan; Zhaohui S. Qin; Liang Zhao 002 (ACM Comput. Surv., 2024)

Structure-based drug design with equivariant diffusion models. - Arne Schneuing; Charles Harris; Yuanqi Du; Kieran Didi; Arian Rokkum Jamasb; Ilia Igashov; Weitao Du; Carla P. Gomes; Tom L. Blundell; Pietro Lio; Max Welling; Michael M. Bronstein; et al. (Nat. Comput. Sci., 2024)

Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. - Lingkai Kong; Yuanqi Du; Wenhao Mu; Kirill Neklyudov; Valentin De Bortoli; Dongxia Wu; Haorui Wang; Aaron M. Ferber; Yian Ma; Carla P. Gomes; Chao Zhang 014 (AISTATS, 2025)

Efficient Evolutionary Search Over Chemical Space with Large Language Models. - Haorui Wang; Marta Skreta; Cher Tian Ser; Wenhao Gao 001; Lingkai Kong; Felix Strieth-Kalthoff; Chenru Duan; Yuchen Zhuang; Yue Yu 001; Yanqiao Zhu 001; Yuanqi Du; Alán Aspuru-Guzik; et al. (ICLR, 2025)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

Optimal transport for generating transition states in chemical reactions. - Chenru Duan; Guan-Horng Liu; Yuanqi Du; Tianrong Chen; Qiyuan Zhao; Haojun Jia; Carla P. Gomes; Evangelos A. Theodorou; Heather J. Kulik (Nat. Mac. Intell., 2025)

Graph Generative Pre-trained Transformer. - Xiaohui Chen; Yinkai Wang; Jiaxing He; Yuanqi Du; Soha Hassoun; Xiaolin Xu; Li-Ping Liu 001 (CoRR, 2025)

AlphaNet: Scaling Up Local Frame-based Atomistic Foundation Model. - Bangchen Yin; Jiaao Wang; Weitao Du; Pengbo Wang; Penghua Ying; Haojun Jia; Zisheng Zhang; Yuanqi Du; Carla P. Gomes; Chenru Duan; Hai Xiao; Graeme Henkelman (CoRR, 2025)

Large Language Model is Secretly a Protein Sequence Optimizer. - Yinkai Wang; Jiaxing He; Yuanqi Du; Xiaohui Chen; Jianan Canal Li; Liping Liu 001; Xiaolin Xu; Soha Hassoun (CoRR, 2025)

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers. - Jiajun He 003; Yuanqi Du; Francisco Vargas 001; Dinghuai Zhang; Shreyas Padhy; Ruikang Ouyang; Carla P. Gomes; José Miguel Hernández-Lobato (CoRR, 2025)

Large Language Models Are Innate Crystal Structure Generators. - Jingru Gan; Peichen Zhong; Yuanqi Du; Yanqiao Zhu 001; Chenru Duan; Haorui Wang; Carla P. Gomes; Kristin A. Persson; Daniel Schwalbe-Koda; Wei Wang 010 (CoRR, 2025)

FEAT: Free energy Estimators with Adaptive Transport. - Jiajun He 003; Yuanqi Du; Francisco Vargas 001; Yuanqing Wang; Carla P. Gomes; José Miguel Hernández-Lobato; Eric Vanden-Eijnden (CoRR, 2025)

LLM-Augmented Chemical Synthesis and Design Decision Programs. - Haorui Wang; Jeff Guo; Lingkai Kong; Rampi Ramprasad; Philippe Schwaller; Yuanqi Du; Chao Zhang 014 (CoRR, 2025)

Building-Block Aware Generative Modeling for 3D Crystals of Metal Organic Frameworks. - Chenru Duan; Aditya Nandy; Sizhan Liu; Yuanqi Du; Liu He; Yi Qu; Haojun Jia; Jin-Hu Dou (CoRR, 2025)

RNE: a plug-and-play framework for diffusion density estimation and inference-time control. - Jiajun He 003; José Miguel Hernández-Lobato; Yuanqi Du; Francisco Vargas 001 (CoRR, 2025)

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 (CoRR, 2025)