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Xiaoning Qian

Professor, ECE & CSE @ Texas A&M


Publications (Google Scholars)

Research Group

Software

Teaching




MS 3128, TAMU
College Station, TX 77843
Office: WERC 205J
Phone: +1 979-845-6268
xqian@ece.tamu.edu

Selected Recent Publications

A more complete list of publications can be referred to Google Scholars
[Note] Supervised students/post-docs are delineated with an asterisk (*).

2024

  • [NeurIPS'24] Keqiang Yan*, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arroyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji. "Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation," The 38th Conference on Neural Information Processing Systems (NeurIPS 2024), December, 2024.

  • [ICPR'24] AmirHossein Rhamati*, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian. "When Uncertainty-based Active Learning May Fail?," The 27th International Conference on Pattern Recognition (ICPR 2024), November, 2024.

  • [ICML'24a] Mingzhou Fan*, Ruida Zhou, Chao Tian, Xiaoning Qian. "Path-Guided Particle-based Sampling," The 41st International Conference on Machine Learning (ICML), 2024.

  • [ICML'24b] Puhua Niu*, Shili Wu, Mingzhou Fan*, Xiaoning Qian. "GFlowNet Training by Policy Gradients," The 41st International Conference on Machine Learning (ICML), 2024.

  • [ICML'24c] Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon. "Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution," The 41st International Conference on Machine Learning (ICML), 2024.

  • [ICML'24d] Keqiang Yan*, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji. "A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction," The 41st International Conference on Machine Learning (ICML), 2024.

  • [KDD'24] Ziyi Zhang, Shaogang Ren*, Xiaoning Qian, Nick Duffield. "Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data," The ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2024.

  • [UAI'24] Mingzhou Fan*, Byung-Jun Yoon, Edward R. Dougherty, Nathan Urban, Francis J. Alexander, Raymundo Arroyave, Xiaoning Qian. "Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity," The 40th International Conference on Uncertainty in Artificial Intelligence (UAI), 2024.

  • [AISTATS'24] Siyuan Xuan*, Yucheng Wang*, Mingzhou Fan*, Byung-Jun Yoon, Xiaoning Qian. "Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting," The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2024.

  • [ICLR'24] Keqiang Yan*, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji. "Complete and Efficient Graph Transformers for Crystal Material Property Prediction," The 12th International Conference on Learning Representations (ICLR), 2024.

  • [ICASSP'24] Sanket Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon. "Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks," The 49th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024.

  • [TMLR'24] Yucheng Wang*, Mingyuan Zhou, Xiaoning Qian. "Hashing with Uncertainty Quantification via Sampling-based Hypothesis Testing," Transactions on Machine Learning Research (TMLR), 2024.

2023

  • [ICML'23a] Haiyang Yu*, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji, "Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian," The 40th International Conference on Machine Learning (ICML), 2023.

  • [ICML'23b] Yuchao Lin, Keqiang Yan*, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji, "Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction," The 40th International Conference on Machine Learning (ICML), 2023.

  • [AISTATS'23] Yucheng Wang*, Mingyuan Zhou, Yu Sun, Xiaoning Qian, "Uncertainty-aware Unsupervised Video Hashing," The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), 2023.

  • [TAI'23] Shahin Boluki*, Siamak Zamani Dadaneh*, Edward Dougherty, Xiaoning Qian, "Bayesian Proper Orthogonal Decomposition for Learnable Reduced-Order Models with Uncertainty Quantification," IEEE Transactions on Artificial Intelligence and Statistics (TAI 2023), 2023.

  • [Patterns'23] Xiaoning Qian, Byung-Jun Yoon, Raymundo Arroyave, Xiaofeng Qian, Edward R. Dougherty. "Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery," Patterns, doi: 10.1016/j.patter.2023.100863, 2023.

2022

  • [ICML'22] Randy Ardywibowo*, Zepeng Huo, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian, "VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty," The 39th International Conference on Machine Learning (ICML 2022), 2022.

  • [AISTATS'22] Randy Ardywibowo*, Shahin Boluki*, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian, "VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition," The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022), 2022.

  • [ICLR'22] Arman Hasanzadeh, Ehsan Hajiramezanali*, Nick Duffield, Xiaoning Qian, "MoReL: Multi-omics Relational Learning," The 10th International Conference on Learning Representations (ICLR 2022), 2022.

  • [ICASSP'22a] Mingzhou Fan*, Byung-Jun Yoon, Francis Alexander, Edward Dougherty, Xiaoning Qian. "Adaptive Group Testing with Mismatched Models," The 47th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2022), 2022.

  • [ICASSP'22b] Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi. "DYNIMP: Dynamic Imputation for Wearable Sensing Data through Sensory and Temporary Relatedness," The 47th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2022), 2022.

  • [Patterns'22] Omar Maddouri*, Xiaoning Qian, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon. "Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning," Patterns, doi: 10.1016/j.patter.2021.100428, 2022.

2021

  • [NeurIPS'21] Guang Zhao*, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian, "Efficient Active Learning for Gaussian Process Classification by Error Reduction," The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), December, 2021.

  • [ICLR'21a] Guang Zhao*, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian, "Uncertainty-aware active learning for optimal Bayesian classifier," The 9th International Conference on Learning Representations (ICLR 2021), May, 2021.

  • [ICLR'21b] Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou, "Contextual dropout: an efficient sample-dependent dropout," The 9th International Conference on Learning Representations (ICLR 2021), May, 2021.

  • [AISTAT'21] Guang Zhao*, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian, "Bayesian active learning by soft mean objective cost of uncertainty," The 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021), April, 2021.

  • [AAAI'21] Ziyu Xiang*, Mingzhou Fan*, Guillermo Vazquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arroyave, Xiaoning Qian. "Physics-constrained automatic feature engineering for predictive modeling in materials science," The 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February, 2021.

  • [Bioinformatics'21a] Shahin Boluki*, Xiaoning Qian, Edward R. Dougherty. "Optimal Bayesian supervised domain adaptation for RNA sequencing data," Bioinformatics, 37(19): 3212-3219, doi: 10.1093/bioinformatics/btab228, 2021.

  • [Bioinformatics'21b] Omar Maddouri*, Xiaoning Qian, Byung-Jun Yoon. "Deep graph representations embed network information for robust disease marker identification," Bioinformatics, in press, doi: 10.1093/bioinformatics/btab772, 2021.

  • [npjCM'21] Bowen Lei, Tanner Quinn Kirk, Anirban Bhattacharya, Debdeep Pati, Xiaoning Qian, Raymundo Arroyave, Bani Mallick. "Bayesian optimization with adaptive surrogate models for automated experimental design," npj Computational Materials, 7(1): 1-12, 2021.

2020

  • [NeurIPS'20] Ehsan Hajiramezanali*, Arman Hasanzadeh, Nick Duffield, Krishna R Narayanan, Xiaoning Qian. "BayReL: Bayesian Relational learning for multi-omics data integration," The 34th Conference on Neural Information Processing Systems (NeurIPS 2020), December, 2020.

  • [BMVC'20] Qing Jin*, Lingjie Yang, Zhenyu Liao, Xiaoning Qian. "Neural network quantization with scale-adjusted training," The 31st British Machine Vision Conference, (BMVC 2020), September, 2020.

  • [ICML'20a] Randy Ardywibowo*, Shahin Boluki*, Xinyu Gong, Zhangyang (Atlas) Wang, Xiaoning Qian. "NADS: Neural Architecture Distribution Search for uncertainty awareness," The 37th International Conference on Machine Learning (ICML 2020), July, 2020.

  • [ICML'20b] Arman Hasanzadeh, Ehsan Hajiramezanali*, Shahin Boluki*, Mingyuan Zhou, Nick Duffield, Krishna R Narayanan, Xiaoning Qian. "Bayesian graph neural networks with adaptive connection sampling," The 37th International Conference on Machine Learning (ICML 2020), July, 2020.

  • [UAI'20] Siamak Zamani Dadaneh*, Shahin Boluki*, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian. "Pairwise supervised Hashing with Bernoulli Variational Auto-Encoder and self-control gradient estimator" The International Conference on Uncertainty in Artificial Intelligence (UAI 2020), August, 2020.

  • [AISTAT'20a] Shahin Boluki*, Randy Ardywibowo*, Siamak Zamani Dadaneh*, Mingyuan Zhou, Xiaoning Qian. "Learnable Bernoulli dropout for Bayesian deep learning," The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020), June, 2020.

  • [AISTAT'20b] Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan Hurley, Ye Yuan, Xiaoning Qian, Zhangyang (Atlas) Wang, Shuai Huang, Bobak Mortazavi. "Uncertainty quantification for deep context-aware mobile activity recognition and unknown context discovery," The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020), June, 2020.

  • [ICASSP'20a] Siamak Zamani Dadaneh*, Shahin Boluki*, Mingyuan Zhou, Xiaoning Qian. "ARSM gradient estimator for supervised learning to rank," The 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), May, 2020.

  • [ICASSP'20b] Ehsan Hajiramezanali*, Arman Hasanzadeh, Nick Duffield, Krishna R Narayanan, Mingyuan Zhou, Xiaoning Qian. "Semi-Implicit Stochastic Recurrent Neural Networks," The 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), May, 2020. *Final list of Best Student Paper Award*

  • [TSP'20] Guang Zhao*, Xiaoning Qian, Byung-Jun Yoon, Francis J. Alexander, Edward R. Dougherty. "Model-based robust filtering and experimental design for stochastic differential equation systems," IEEE Transactions on Signal Processing (TSP), 68: 3849-3859, 2020.

2019

  • [NeurIPS'19a] Ehsan Hajiramezanali*, Arman Hasanzadeh, Nick Duffield, Krishna R Narayanan, Mingyuan Zhou, Xiaoning Qian. "Variational Graph Recurrent Neural Networks," The 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), December, 2019.

  • [NeurIPS'19b] Arman Hasanzadeh, Ehsan Hajiramezanali*, Nick Duffield, Krishna R Narayanan, Mingyuan Zhou, Xiaoning Qian. "Semi-Implicit Graph Variational Auto-Encoders," The 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), December, 2019.

  • [CVPR'19] Wuyang Chen, Ziyu Jiang, Zhangyang (Atlas) Wang, Kexin Cui, Xiaoning Qian. "Collaborative global-local networks for memory-efficient segmentation of ultra-high resolution images," The IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), June, 2019.

  • [AISTAT'19] Randy Ardywibowo*, Guang Zhao*, Zhangyang (Atlas) Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian. "Adaptive activity monitoring with uncertainty quantification in switching Gaussian Process models," The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), April, 2019.

  • [Bioinformatics'19] Chun-Chi (Aky) Chen*, Hyundoo Jeong*, Xiaoning Qian, Byung-Jun Yoon. "TOPAS: network-based structural alignment of RNA sequences," Bioinformatics, in press, doi: 10.1093/bioinformatics/btz001, 2019.

  • [TIP'19] Chung-Chi (Charles) Tsai*, Weizhi Li*, Kuang-Jui Hsu, Xiaoning Qian, Yen-Yu Lin. "Image co-saliency detection and co-segmentation via progressive joint optimization," IEEE Transactions on Image Processing (TIP), 28(1):56--71, 2019.

2018

  • [NeurIPS'18] Ehsan Hajiramezanali*, Siamak Zamani Dadaneh*, Alireza Karbalayghareh*, Mingyuan Zhou, Xiaoning Qian. "Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data," The 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), December, 2018.

  • [ECCV'18] Kuang-Jui Hsu, Chung-Chi (Charles) Tsai*, Yen-Yu Lin, Xiaoning Qian, Yung-Yu Chuang. "Unsupervised CNN-based co-saliency detection with graphical optimization," The 15th European Conference on Computer Vision (ECCV 2018), September, 2018.

  • [ISMB'18] Siamak Zamani Dadaneh*, Mingyuan Zhou, Xiaoning Qian. "Covariate-dependent negative binomial factor analysis of RNA sequencing data," The 26th International Conference on Intelligent Systems for Molecular Biology (ISMB 2018), July, 2018.

  • [PRM'18] Anjana Talapatra, Shahin Boluki*, T Duong, Xiaoning Qian, Edward R. Dougherty, Raymundo Arroyave. "Autonomous efficient experiment design for materials discovery with Bayesian model averaging," Physical Review Materials (PRM), 2(11):113803, 2018.

  • [Bioinformatics'18] Siamak Zamani Dadaneh*, Mingyuan Zhou, Xiaoning Qian. "Bayesian negative binomial regression for differential expression with confounding factors," Bioinformatics, 34(19):3349--3356, 2018.

  • [MD'18] Alexandros Solomou, Guang Zhao*, Shahin Boluki*, Jobin K Joy, Xiaoning Qian, Ibrahim Karaman, Raymundo Arroyave, Dimitris C Lagoudas. "Multi-objective Bayesian materials discovery: Application on the discovery of precipitation strengthened NiTi shape memory alloys through micromechanical modeling," Materials & Design (MD), 160:810--817, 2018.

  • [TPAMI'18] Shaogang Ren*, Shuai Huang, Jieping Ye, Xiaoning Qian. "Safe feature screening for generalized LASSO," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 40(12):2992--3006, 2018.

  • [TSP'18a] Siamak Zamani Dadaneh*, Edward R. Dougherty, Xiaoning Qian. "Optimal Bayesian classification with missing values," IEEE Transactions on Signal Processing (TSP), 66(16):4182--4192, 2018.

  • [TSP'18b] Alireza Karbalayghareh*, Xiaoning Qian, Edward R. Dougherty. "Optimal Bayesian transfer learning," IEEE Transactions on Signal Processing (TSP), 66(14):3724--3739, 2018.

  • [JASA'18] Siamak Zamani Dadaneh*, Xiaoning Qian, Mingyuan Zhou. "BNP-Seq: Bayesian nonparametric differential expression analysis of sequencing count data," Journal of the American Statistical Association (JASA), 113(521):81--94, 2018.

  • [PR'18] Lucia Xiaopeng Sui*, Easton Li Xu*, Xiaoning Qian, Tie Liu. "Convex clustering with metric learning," Pattern Recognition (PR), 81:575--584, 2018.

  • [TSP'18c] Roozbeh Dehghannasiri*, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty. "Optimal Bayesian Kalman filtering with prior update," IEEE Transactions on Signal Processing (TSP), 66(8):1982--1996, 2018.

© January 2023 Xiaoning Qian