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Journal Articles
- 2024
[j9]Shiyu Wang
, Yuanqi Du, Xiaojie Guo, Bo Pan, Zhaohui S. Qin, Liang Zhao:
Controllable Data Generation by Deep Learning: A Review. ACM Comput. Surv. 56(9): 228:1-228:38 (2024)- [j8]Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu:
Molecular Contrastive Pretraining with Collaborative Featurizations. J. Chem. Inf. Model. 64(4): 1112-1122 (2024) - [j7]Yuanqi Du, Arian R. Jamasb, Jeff Guo, Tianfan Fu, Charles Harris, Yingheng Wang, Chenru Duan, Pietro Liò, Philippe Schwaller, Tom L. Blundell:
Machine learning-aided generative molecular design. Nat. Mac. Intell. 6(6): 589-604 (2024) - [j6]Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang:
MUBen: Benchmarking the Uncertainty of Molecular Representation Models. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j5]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [j4]Chenru Duan, Yuanqi Du, Haojun Jia, Heather J. Kulik:
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. Nat. Comput. Sci. 3(12): 1045-1055 (2023) - [j3]Yuanqi Du, Xian Liu, Nilay Mahesh Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou:
ChemSpacE: Interpretable and Interactive Chemical Space Exploration. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j2]Yuanqi Du, Xiaojie Guo, Yinkai Wang, Amarda Shehu, Liang Zhao:
Small molecule generation via disentangled representation learning. Bioinform. 38(12): 3200-3208 (2022) - 2021
- [j1]Pengbo Liu, Hu Han, Yuanqi Du, Heqin Zhu, Yinhao Li, Feng Gu, Honghu Xiao, Jun Li, Chunpeng Zhao, Li Xiao, Xinbao Wu, S. Kevin Zhou:
Deep learning to segment pelvic bones: large-scale CT datasets and baseline models. Int. J. Comput. Assist. Radiol. Surg. 16(5): 749-756 (2021)
Conference and Workshop Papers
- 2024
- [c30]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. ICLR 2024 - 2023
- [c29]Weitao Du, He Zhang, Tao Yang, Yuanqi Du:
A Flexible Diffusion Model. ICML 2023: 8678-8696 - [c28]Dieqiao Feng, Yuanqi Du, Carla P. Gomes, Bart Selman:
Weighted Sampling without Replacement for Deep Top-k Classification. ICML 2023: 9910-9920 - [c27]Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li:
A Systematic Survey of Chemical Pre-trained Models. IJCAI 2023: 6787-6795 - [c26]Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan:
The Second Learning on Graphs Conference: Preface. LoG 2023: i-xix - [c25]Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang:
Uncovering Neural Scaling Laws in Molecular Representation Learning. NeurIPS 2023 - [c24]Xiaohui Chen, Yinkai Wang, Yuanqi Du, Soha Hassoun, Liping Liu:
On Separate Normalization in Self-supervised Transformers. NeurIPS 2023 - [c23]Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma:
A new perspective on building efficient and expressive 3D equivariant graph neural networks. NeurIPS 2023 - [c22]Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John M. Gregoire, Carla Pedro Gomes:
M2Hub: Unlocking the Potential of Machine Learning for Materials Discovery. NeurIPS 2023 - [c21]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, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang:
GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS 2023 - [c20]Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling:
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths. NeurIPS 2023 - [c19]Runsheng Xu, Zhengzhong Tu, Yuanqi Du, Xiaoyu Dong, Jinlong Li, Zibo Meng, Jiaqi Ma, Alan C. Bovik, Hongkai Yu:
Pik-Fix: Restoring and Colorizing Old Photos. WACV 2023: 1724-1734 - 2022
- [c18]Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao:
Disentangled Spatiotemporal Graph Generative Models. AAAI 2022: 6541-6549 - [c17]Bo Pan, Yinkai Wang, Xuanyang Lin, Muran Qin, Yuanqi Du, Shiva Ghaemi, Aowei Ding, Shiyu Wang, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Ashley Ann Petersen, Austin Leitgeb, Amarda Shehu, Liang Zhao:
Property-Controllable Generation of Quaternary Ammonium Compounds. BIBM 2022: 3462-3469 - [c16]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu:
SE(3) Equivariant Graph Neural Networks with Complete Local Frames. ICML 2022: 5583-5608 - [c15]Yuanqi Du, Quan Quan, Hu Han, S. Kevin Zhou:
Semi-Supervised Pseudo-Healthy Image Synthesis via Confidence Augmentation. ISBI 2022: 1-4 - [c14]Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu:
A Survey on Deep Graph Generation: Methods and Applications. LoG 2022: 47 - [c13]Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov:
The First Learning on Graphs Conference: Preface. LoG 2022: i-xxiii - [c12]Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell:
Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks. NeurIPS 2022 - [c11]Xian Liu, Qianyi Wu, Hang Zhou, Yuanqi Du, Wayne Wu, Dahua Lin, Ziwei Liu:
Audio-Driven Co-Speech Gesture Video Generation. NeurIPS 2022 - [c10]Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Amarda Shehu, Liang Zhao:
Multi-objective Deep Data Generation with Correlated Property Control. NeurIPS 2022 - [c9]Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Interpretable Molecular Graph Generation via Monotonic Constraints. SDM 2022: 73-81 - 2021
- [c8]Yuanqi Du, Yinkai Wang, Fardina Fathmiul Alam, Yuanjie Lu, Xiaojie Guo, Liang Zhao, Amarda Shehu:
Deep Latent-Variable Models for Controllable Molecule Generation. BIBM 2021: 372-375 - [c7]Yinkai Wang, Aowei Ding, Kaiyi Guan, Yuanqi Du:
Ensemble Machine Learning System for Student AcademicPerformance Prediction. EDM (Workshops) 2021 - [c6]Taseef Rahman, Yuanqi Du, Amarda Shehu:
Graph Representation Learning for Protein Conformation Sampling. ICCABS 2021: 16-28 - [c5]Xiaojie Guo, Yuanqi Du, Liang Zhao:
Property Controllable Variational Autoencoder via Invertible Mutual Dependence. ICLR 2021 - [c4]Xiaojie Guo, Yuanqi Du, Liang Zhao:
Deep Generative Models for Spatial Networks. KDD 2021: 505-515 - [c3]Yuanqi Du, Shiyu Wang, Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang, Aishwarya Varala, Abhinav Angirekula, Liang Zhao:
GraphGT: Machine Learning Datasets for Graph Generation and Transformation. NeurIPS Datasets and Benchmarks 2021 - 2020
- [c2]Yuanqi Du, Nguyen Dang, Riley Wilkerson, Parth H. Pathak, Huzefa Rangwala, Jana Kosecka:
American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract). AAAI 2020: 13781-13782 - [c1]Panneer Selvam Santhalingam, Yuanqi Du, Riley Wilkerson, Al Amin Hosain, Ding Zhang, Parth H. Pathak, Huzefa Rangwala, Raja S. Kushalnagar:
Expressive ASL Recognition using Millimeter-wave Wireless Signals. SECON 2020: 1-9
Data and Artifacts
- 2021
- [d2]Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Dataset for Disentangled Representation Learning for Interpretable Molecule Generation. IEEE DataPort, 2021
- [d1]Taseef Rahman, Yuanqi Du, Liang Zhao, Amarda Shehu:
Dataset for Generative Adversarial Learning of Protein Tertiary Structures. Molecules, 2021. IEEE DataPort, 2021
Informal and Other Publications
- 2024
- [i36]Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortol, Haorui Wang, Dongxia Wu, Aaron Ferber, Yi-An Ma, Carla P. Gomes, Chao Zhang:
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. CoRR abs/2402.18012 (2024) - [i35]Chenru Duan, Guan-Horng Liu, Yuanqi Du, Tianrong Chen, Qiyuan Zhao, Haojun Jia, Carla P. Gomes, Evangelos A. Theodorou, Heather J. Kulik:
React-OT: Optimal Transport for Generating Transition State in Chemical Reactions. CoRR abs/2404.13430 (2024) - [i34]Guanghao Wei, Yining Huang, Chenru Duan, Yue Song, Yuanqi Du:
Navigating Chemical Space with Latent Flows. CoRR abs/2405.03987 (2024) - [i33]Lingkai Kong, Haorui Wang, Wenhao Mu, Yuanqi Du, Yuchen Zhuang, Yifei Zhou, Yue Song, Rongzhi Zhang, Kai Wang, Chao Zhang:
Aligning Large Language Models with Representation Editing: A Control Perspective. CoRR abs/2406.05954 (2024) - [i32]Haorui Wang, Marta Skreta, Cher-Tian Ser, Wenhao Gao, Lingkai Kong, Felix Streith-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang:
Efficient Evolutionary Search Over Chemical Space with Large Language Models. CoRR abs/2406.16976 (2024) - 2023
- [i31]Junwen Bai, Yuanqi Du, Yingheng Wang, Shufeng Kong, John M. Gregoire, Carla Gomes:
Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction. CoRR abs/2302.01486 (2023) - [i30]Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma:
A new perspective on building efficient and expressive 3D equivariant graph neural networks. CoRR abs/2304.04757 (2023) - [i29]Chenru Duan, Yuanqi Du, Haojun Jia, Heather J. Kulik:
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. CoRR abs/2304.06174 (2023) - [i28]Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang:
MUBen: Benchmarking the Uncertainty of Pre-Trained Models for Molecular Property Prediction. CoRR abs/2306.10060 (2023) - [i27]Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John M. Gregoire, Carla P. Gomes:
M2Hub: Unlocking the Potential of Machine Learning for Materials Discovery. CoRR abs/2307.05378 (2023) - [i26]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i25]Xiaohui Chen, Yinkai Wang, Yuanqi Du, Soha Hassoun, Li-Ping Liu:
On Separate Normalization in Self-supervised Transformers. CoRR abs/2309.12931 (2023) - [i24]Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang:
Uncovering Neural Scaling Laws in Molecular Representation Learning. CoRR abs/2309.15123 (2023) - [i23]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. CoRR abs/2310.00115 (2023) - 2022
- [i22]Jun Xia, Yanqiao Zhu, Yuanqi Du, Stan Z. Li:
A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications. CoRR abs/2202.07893 (2022) - [i21]Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao:
Disentangled Spatiotemporal Graph Generative Models. CoRR abs/2203.00411 (2022) - [i20]Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao:
Interpretable Molecular Graph Generation via Monotonic Constraints. CoRR abs/2203.00412 (2022) - [i19]Quan Quan, Qiyuan Wang, Yuanqi Du, Liu Li, S. Kevin Zhou:
Recovering medical images from CT film photos. CoRR abs/2203.05567 (2022) - [i18]Yanqiao Zhu, Yuanqi Du, Yinkai Wang, Yichen Xu, Jieyu Zhang, Qiang Liu, Shu Wu:
A Survey on Deep Graph Generation: Methods and Applications. CoRR abs/2203.06714 (2022) - [i17]Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu:
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. CoRR abs/2203.14500 (2022) - [i16]Runsheng Xu, Zhengzhong Tu, Yuanqi Du, Xiaoyu Dong, Jinlong Li, Zibo Meng, Jiaqi Ma, Alan C. Bovik, Hongkai Yu:
Pik-Fix: Restoring and Colorizing Old Photos. CoRR abs/2205.01902 (2022) - [i15]Weitao Du, Tao Yang, He Zhang, Yuanqi Du:
A Flexible Diffusion Model. CoRR abs/2206.10365 (2022) - [i14]Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling:
Path Integral Stochastic Optimal Control for Sampling Transition Paths. CoRR abs/2207.02149 (2022) - [i13]Shiyu Wang, Yuanqi Du, Xiaojie Guo, Bo Pan, Liang Zhao:
Controllable Data Generation by Deep Learning: A Review. CoRR abs/2207.09542 (2022) - [i12]Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu:
Improving Molecular Pretraining with Complementary Featurizations. CoRR abs/2209.15101 (2022) - [i11]Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Amarda Shehu, Liang Zhao:
Multi-objective Deep Data Generation with Correlated Property Control. CoRR abs/2210.01796 (2022) - [i10]Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Structure-based Drug Design with Equivariant Diffusion Models. CoRR abs/2210.13695 (2022) - [i9]Jun Xia, Yanqiao Zhu, Yuanqi Du, Yue Liu, Stan Z. Li:
A Systematic Survey of Molecular Pre-trained Models. CoRR abs/2210.16484 (2022) - [i8]Xian Liu, Qianyi Wu, Hang Zhou, Yuanqi Du, Wayne Wu, Dahua Lin, Ziwei Liu:
Audio-Driven Co-Speech Gesture Video Generation. CoRR abs/2212.02350 (2022) - [i7]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, Alex Chan, Jacob Moss, Chengzhi Guo, Alpha A. Lee, Philippe Schwaller, Jian Tang:
GAUCHE: A Library for Gaussian Processes in Chemistry. CoRR abs/2212.04450 (2022) - 2021
- [i6]Yuanqi Du, Quan Quan, Hu Han, S. Kevin Zhou:
Where is the disease? Semi-supervised pseudo-normality synthesis from an abnormal image. CoRR abs/2106.15345 (2021) - [i5]Ziming Liu, Yunyue Chen, Yuanqi Du, Max Tegmark:
Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning. CoRR abs/2109.13901 (2021) - [i4]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu:
Equivariant vector field network for many-body system modeling. CoRR abs/2110.14811 (2021) - [i3]Yinkai Wang, Aowei Ding, Kaiyi Guan, Shixi Wu, Yuanqi Du:
Graph-based Ensemble Machine Learning for Student Performance Prediction. CoRR abs/2112.07893 (2021) - 2020
- [i2]Pengbo Liu, Hu Han, Yuanqi Du, Heqin Zhu, Yinhao Li, Feng Gu, Honghu Xiao, Jun Li, Chunpeng Zhao, Li Xiao, Xinbao Wu, S. Kevin Zhou:
Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models. CoRR abs/2012.08721 (2020) - [i1]Quan Quan, Qiyuan Wang, Liu Li, Yuanqi Du, S. Kevin Zhou:
CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models. CoRR abs/2012.09491 (2020)
Coauthor Index
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