Xiaoning Qian

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 168

Top Venues

Publications

Siyuan Xu, Yucheng Wang, Mingzhou Fan, Byung-Jun Yoon, Xiaoning Qian
Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting. AISTATS (2024)
Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. CoRR (2024)
Xihaier Luo, Seyednami Niyakan, Patrick R. Johnstone, Sean McCorkle, Gilchan Park, Vanessa López-Marrero, Shinjae Yoo, Edward R. Dougherty, Xiaoning Qian, Francis J. Alexander, Shantenu Jha, Byung-Jun Yoon
Pathway-based analyses of gene expression profiles at low doses of ionizing radiation. Frontiers Bioinform. 4 (2024)
Shahin Boluki, Siamak Zamani Dadaneh, Edward R. Dougherty, Xiaoning Qian
Bayesian Proper Orthogonal Decomposition for Learnable Reduced-Order Models With Uncertainty Quantification. IEEE Trans. Artif. Intell. 5 (3) (2024)
Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
Multi-modal Representation Learning for Cross-modal Prediction of Continuous Weather Patterns from Discrete Low-Dimensional Data. CoRR (2024)
Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks. ICASSP (2024)
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Complete and Efficient Graph Transformers for Crystal Material Property Prediction. ICLR (2024)
Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data. KDD (2024)
Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield
Towards Invariant Time Series Forecasting in Smart Cities. CoRR (2024)
Shaogang Ren, Xiaoning Qian
Dynamic Incremental Optimization for Best Subset Selection. CoRR (2024)
Shaogang Ren, Xiaoning Qian
Causal Bayesian Optimization via Exogenous Distribution Learning. CoRR (2024)
Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution. CoRR (2024)
Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data. CoRR (2024)
Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield
Towards Invariant Time Series Forecasting in Smart Cities. WWW (Companion Volume) (2024)
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Complete and Efficient Graph Transformers for Crystal Material Property Prediction. CoRR (2024)
Seyednami Niyakan, Jianting Sheng, Yuliang Cao, Xiang Zhang, Zhan Xu, Ling Wu, Stephen T. C. Wong, Xiaoning Qian
MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance. Patterns 5 (6) (2024)
Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. ICML (2023)
Alif Bin Abdul Qayyum, Xiaoning Qian, Byung-Jun Yoon
Enhancing Cryo-EM Particle Picking Through Consistency Model-based Latent Space Denoiser. BCB (2023)
Xihaier Luo, Sean McCorkle, Gilchan Park, Vanessa López-Marrero, Shinjae Yoo, Edward R. Dougherty, Xiaoning Qian, Francis J. Alexander, Byung-Jun Yoon
Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response. CoRR (2023)
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. CoRR (2023)
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. CoRR (2023)
Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji
A Latent Diffusion Model for Protein Structure Generation. LoG (2023)
Francis J. Alexander, Meifeng Lin, Xiaoning Qian, Byung-Jun Yoon
Accelerating scientific discoveries through data-driven innovations. Patterns 4 (11) (2023)
Puhua Niu, Maria J. Soto, Shuai Huang, Byung-Jun Yoon, Edward R. Dougherty, Francis J. Alexander, Ian Blaby, Xiaoning Qian
Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction. J. Comput. Biol. 30 (7) (2023)
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 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 (2023)
Hyun-Myung Woo, Xiaoning Qian, Li Tan, Shantenu Jha, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon
Optimal decision-making in high-throughput virtual screening pipelines. Patterns 4 (11) (2023)
Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji
A Latent Diffusion Model for Protein Structure Generation. CoRR (2023)
Xiaoning Qian, Byung-Jun Yoon, Raymundo Arróyave, Xiaofeng Qian, Edward R. Dougherty
Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery. Patterns 4 (11) (2023)
Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian
Uncertainty-aware Unsupervised Video Hashing. AISTATS (2023)
Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks. CoRR (2023)
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML (2023)
Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. CoRR (2023)
Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon
Geometric Affinity Propagation for Clustering With Network Knowledge. IEEE Trans. Knowl. Data Eng. 35 (11) (2023)
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. NeurIPS (2023)
Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi
DynImp: Dynamic Imputation for Wearable Sensing Data Through Sensory and Temporal Relatedness. CoRR (2022)
Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition. AISTATS (2022)
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. CoRR (2022)
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian
MoReL: Multi-omics Relational Learning. CoRR (2022)
Xihaier Luo, Sean McCorkle, Gilchan Park, Vanessa López-Marrero, Shinjae Yoo, Edward R. Dougherty, Xiaoning Qian, Francis J. Alexander, Byung-Jun Yoon
Comprehensive analysis of gene expression profiles to radiation exposure reveals molecular signatures of low-dose radiation response. BIBM (2022)
Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon
Deep graph representations embed network information for robust disease marker identification. Bioinform. 38 (4) (2022)
Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak Mortazavi
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. CoRR (2022)
Yucheng Wang, Mengmeng Gu, Mingyuan Zhou, Xiaoning Qian
Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. SenSys (2022)
Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi
Dynimp: Dynamic Imputation for Wearable Sensing Data through Sensory and Temporal Relatedness. ICASSP (2022)
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian
MoReL: Multi-omics Relational Learning. ICLR (2022)
Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. MLHC (2022)
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 3 (3) (2022)
Randy Ardywibowo, Zepeng Huo, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian
VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty. ICML (2022)
Mingzhou Fan, Byung-Jun Yoon, Francis J. Alexander, Edward R. Dougherty, Xiaoning Qian
Adaptive Group Testing with Mismatched Models. ICASSP (2022)
Shahin Boluki, Xiaoning Qian, Edward R. Dougherty
Optimal Bayesian supervised domain adaptation for RNA sequencing data. Bioinform. 37 (19) (2021)
Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. CoRR (2021)
Seyednami Niyakan, Xiaoning Qian
COVID-Datathon: Biomarker identification for COVID-19 severity based on BALF scRNA-seq data. CoRR (2021)
Xuan Dang, Shuai Huang, Xiaoning Qian
Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors. Stat. Comput. 31 (6) (2021)
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. CoRR (2021)
Ziyu Xiang, Mingzhou Fan, Guillermo Vázquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arróyave, Xiaoning Qian
Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science. AAAI (2021)
Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian
Efficient Active Learning for Gaussian Process Classification by Error Reduction. NeurIPS (2021)
Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon
Geometric Affinity Propagation for Clustering with Network Knowledge. CoRR (2021)
Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian
Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty. AISTATS (2021)
Ameer Hamza Shakur, Shuai Huang, Xiaoning Qian, Xiangyu Chang
SURVFIT: Doubly sparse rule learning for survival data. J. Biomed. Informatics 117 (2021)
Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. ICLR (2021)
Byung-Jun Yoon, Xiaoning Qian, Edward R. Dougherty
Quantifying the Multi-Objective Cost of Uncertainty. IEEE Access 9 (2021)
Hyun-Myung Woo, Xiaoning Qian, Li Tan, Shantenu Jha, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon
Optimal Decision Making in High-Throughput Virtual Screening Pipelines. CoRR (2021)
Zepeng Huo, Lida Zhang, Rohan Khera, Shuai Huang, Xiaoning Qian, Zhangyang Wang, Bobak J. Mortazavi
Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data. BHI (2021)
Xuan Dang, Shuai Huang, Xiaoning Qian
Risk Factor Identification in Heterogeneous Disease Progression with L1-Regularized Multi-state Models. J. Heal. Informatics Res. 5 (1) (2021)
Alireza Karbalayghareh, Xiaoning Qian, Edward R. Dougherty
Optimal Bayesian Transfer Learning for Count Data. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (2) (2021)
Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian
Uncertainty-aware Active Learning for Optimal Bayesian Classifier. ICLR (2021)
Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian
Learnable Bernoulli Dropout for Bayesian Deep Learning. AISTATS (2020)
Ameer Hamza Shakur, Xiaoning Qian, Zhangyang Wang, Bobak Mortazavi, Shuai Huang
GPSRL: Learning Semi-Parametric Bayesian Survival Rule Lists from Heterogeneous Patient Data. ICPR (2020)
Byung-Jun Yoon, Xiaoning Qian, Edward R. Dougherty
Quantifying the multi-objective cost of uncertainty. CoRR (2020)
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian
Bayesian Graph Neural Networks with Adaptive Connection Sampling. ICML (2020)
Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
NADS: Neural Architecture Distribution Search for Uncertainty Awareness. ICML (2020)
Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian
Bayesian Graph Neural Networks with Adaptive Connection Sampling. CoRR (2020)
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 Trans. Signal Process. 68 (2020)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. NeurIPS (2020)
Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian
Learnable Bernoulli Dropout for Bayesian Deep Learning. CoRR (2020)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Stochastic Recurrent Neural Networks. ICASSP (2020)
Qing Jin, Linjie Yang, Zhenyu Liao, Xiaoning Qian
Neural Network Quantization with Scale-Adjusted Training. BMVC (2020)
Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. UAI (2020)
Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian
Arsm Gradient Estimator for Supervised Learning to Rank. ICASSP (2020)
Yijie Wang, Hyundoo Jeong, Byung-Jun Yoon, Xiaoning Qian
ClusterM: a scalable algorithm for computational prediction of conserved protein complexes across multiple protein interaction networks. BMC Genom. 21 (S-10) (2020)
Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
NADS: Neural Architecture Distribution Search for Uncertainty Awareness. CoRR (2020)
Meltem Apaydin, Liang Xu, Bo Zeng, Xiaoning Qian
Pessimistic optimisation for modelling microbial communities with uncertainty. Int. J. Comput. Biol. Drug Des. 13 (1) (2020)
Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. AISTATS (2020)
Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. CoRR (2020)
Chung-Chi Tsai, Kuang-Jui Hsu, Yen-Yu Lin, Xiaoning Qian, Yung-Yu Chuang
Deep Co-Saliency Detection via Stacked Autoencoder-Enabled Fusion and Self-Trained CNNs. IEEE Trans. Multim. 22 (4) (2020)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Xiaoning Qian
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. CoRR (2020)
Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. CoRR (2020)
Kai He, Shuai Huang, Xiaoning Qian
Early detection and risk assessment for chronic disease with irregular longitudinal data analysis. J. Biomed. Informatics 96 (2019)
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Graph Variational Auto-Encoders. CoRR (2019)
Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. AISTATS (2019)
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian
Variational Graph Recurrent Neural Networks. CoRR (2019)
Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian
Variational Graph Recurrent Neural Networks. NeurIPS (2019)
Chun-Chi Chen, Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon
TOPAS: network-based structural alignment of RNA sequences. Bioinform. 35 (17) (2019)
Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty
Optimal clustering with missing values. BMC Bioinform. (12) (2019)
Chun-Chi Chen, Xiaoning Qian, Byung-Jun Yoon
RNAdetect: efficient computational detection of novel non-coding RNAs. Bioinform. 35 (7) (2019)
Wuyang Chen, Ziyu Jiang, Zhangyang Wang, Kexin Cui, Xiaoning Qian
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images. CVPR (2019)
Shahin Boluki, Xiaoning Qian, Edward R. Dougherty
Experimental Design via Generalized Mean Objective Cost of Uncertainty. IEEE Access 7 (2019)
Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian
ARSM Gradient Estimator for Supervised Learning to Rank. CoRR (2019)
Shahin Boluki, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty
Constructing Pathway-Based Priors within a Gaussian Mixture Model for Bayesian Regression and Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (2) (2019)
Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian
Semi-Implicit Graph Variational Auto-Encoders. NeurIPS (2019)
Tianshu Feng, Xiaoning Qian, Kaibo Liu, Shuai Huang
Dynamic Inspection of Latent Variables in State-Space Systems. IEEE Trans Autom. Sci. Eng. 16 (3) (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Xiaoning Qian