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Xiaoning Qian
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2020 – today
- 2024
- [j88]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) - [j87]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): 100986 (2024) - [j86]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): 1162-1173 (2024) - [c99]Siyuan Xu, Yucheng Wang, Mingzhou Fan, Byung-Jun Yoon, Xiaoning Qian:
Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting. AISTATS 2024: 4105-4113 - [c98]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: 5330-5334 - [c97]Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Complete and Efficient Graph Transformers for Crystal Material Property Prediction. ICLR 2024 - [c96]Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian:
Path-Guided Particle-based Sampling. ICML 2024 - [c95]Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon:
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution. ICML 2024 - [c94]Puhua Niu, Shili Wu, Mingzhou Fan, Xiaoning Qian:
GFlowNet Training by Policy Gradients. ICML 2024 - [c93]Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. ICML 2024 - [c92]Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield:
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data. KDD 2024: 4408-4418 - [c91]Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield:
Towards Invariant Time Series Forecasting in Smart Cities. WWW (Companion Volume) 2024: 1344-1350 - [i48]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 abs/2401.16936 (2024) - [i47]Shaogang Ren, Xiaoning Qian:
Causal Bayesian Optimization via Exogenous Distribution Learning. CoRR abs/2402.02277 (2024) - [i46]Shaogang Ren, Xiaoning Qian:
Dynamic Incremental Optimization for Best Subset Selection. CoRR abs/2402.02322 (2024) - [i45]Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Complete and Efficient Graph Transformers for Crystal Material Property Prediction. CoRR abs/2403.11857 (2024) - [i44]Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield:
Towards Invariant Time Series Forecasting in Smart Cities. CoRR abs/2405.05430 (2024) - [i43]Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon:
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution. CoRR abs/2405.12202 (2024) - [i42]Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield:
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data. CoRR abs/2406.10419 (2024) - [i41]Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. CoRR abs/2406.12888 (2024) - [i40]Puhua Niu, Shili Wu, Mingzhou Fan, Xiaoning Qian:
GFlowNet Training by Policy Gradients. CoRR abs/2408.05885 (2024) - [i39]Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian:
Understanding Uncertainty-based Active Learning Under Model Mismatch. CoRR abs/2408.13690 (2024) - [i38]Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon:
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data. CoRR abs/2409.17367 (2024) - 2023
- [j85]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): 751-765 (2023) - [j84]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): 100863 (2023) - [j83]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): 100875 (2023) - [j82]Francis J. Alexander, Meifeng Lin, Xiaoning Qian, Byung-Jun Yoon:
Accelerating scientific discoveries through data-driven innovations. Patterns 4(11): 100876 (2023) - [j81]Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon:
Geometric Affinity Propagation for Clustering With Network Knowledge. IEEE Trans. Knowl. Data Eng. 35(11): 11419-11436 (2023) - [c90]Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian:
Uncertainty-aware Unsupervised Video Hashing. AISTATS 2023: 6722-6740 - [c89]Alif Bin Abdul Qayyum, Xiaoning Qian, Byung-Jun Yoon:
Enhancing Cryo-EM Particle Picking Through Consistency Model-based Latent Space Denoiser. BCB 2023: 72:1 - [c88]Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji:
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. ICML 2023: 21260-21287 - [c87]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML 2023: 40412-40424 - [c86]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: 29 - [c85]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 - [i37]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 abs/2301.01769 (2023) - [i36]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 abs/2305.04120 (2023) - [i35]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. CoRR abs/2306.04922 (2023) - [i34]Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. CoRR abs/2306.09549 (2023) - [i33]Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji:
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. CoRR abs/2306.10045 (2023) - [i32]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) - [i31]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 abs/2309.03061 (2023) - 2022
- [j80]Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon:
Deep graph representations embed network information for robust disease marker identification. Bioinform. 38(4): 1075-1086 (2022) - [j79]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): 100428 (2022) - [c84]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: 1359-1379 - [c83]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: 2366-2374 - [c82]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: 3988-3992 - [c81]Mingzhou Fan, Byung-Jun Yoon, Francis J. Alexander, Edward R. Dougherty, Xiaoning Qian:
Adaptive Group Testing with Mismatched Models. ICASSP 2022: 4533-4537 - [c80]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian:
MoReL: Multi-omics Relational Learning. ICLR 2022 - [c79]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: 865-877 - [c78]Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi:
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. MLHC 2022: 101-122 - [c77]Yucheng Wang, Mengmeng Gu, Mingyuan Zhou, Xiaoning Qian:
Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. SenSys 2022: 1109-1115 - [i30]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian:
MoReL: Multi-omics Relational Learning. CoRR abs/2203.08149 (2022) - [i29]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 abs/2204.00130 (2022) - [i28]Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak Mortazavi:
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. CoRR abs/2207.11382 (2022) - [i27]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 abs/2209.15415 (2022) - 2021
- [j78]Byung-Jun Yoon, Xiaoning Qian, Edward R. Dougherty:
Quantifying the Multi-Objective Cost of Uncertainty. IEEE Access 9: 80351-80359 (2021) - [j77]Shahin Boluki, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian supervised domain adaptation for RNA sequencing data. Bioinform. 37(19): 3212-3219 (2021) - [j76]Ameer Hamza Shakur, Shuai Huang, Xiaoning Qian, Xiangyu Chang:
SURVFIT: Doubly sparse rule learning for survival data. J. Biomed. Informatics 117: 103691 (2021) - [j75]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): 20-53 (2021) - [j74]Xuan Dang, Shuai Huang, Xiaoning Qian:
Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors. Stat. Comput. 31(6): 77 (2021) - [j73]Alireza Karbalayghareh, Xiaoning Qian, Edward R. Dougherty:
Optimal Bayesian Transfer Learning for Count Data. IEEE ACM Trans. Comput. Biol. Bioinform. 18(2): 644-655 (2021) - [c76]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: 10414-10421 - [c75]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: 3970-3978 - [c74]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: 1-4 - [c73]Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou:
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. ICLR 2021 - [c72]Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian:
Uncertainty-aware Active Learning for Optimal Bayesian Classifier. ICLR 2021 - [c71]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: 9734-9746 - [i26]Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou:
Contextual Dropout: An Efficient Sample-Dependent Dropout Module. CoRR abs/2103.04181 (2021) - [i25]Omar Maddouri, Xiaoning Qian, Byung-Jun Yoon:
Geometric Affinity Propagation for Clustering with Network Knowledge. CoRR abs/2103.14376 (2021) - [i24]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 abs/2109.02150 (2021) - [i23]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 abs/2109.11683 (2021) - [i22]Seyednami Niyakan, Xiaoning Qian:
COVID-Datathon: Biomarker identification for COVID-19 severity based on BALF scRNA-seq data. CoRR abs/2110.04986 (2021) - 2020
- [j72]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) - [j71]Meltem Apaydin, Liang Xu, Bo Zeng, Xiaoning Qian:
Pessimistic optimisation for modelling microbial communities with uncertainty. Int. J. Comput. Biol. Drug Des. 13(1): 82-97 (2020) - [j70]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): 1016-1031 (2020) - [j69]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: 3849-3859 (2020) - [c70]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: 3894-3904 - [c69]Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Learnable Bernoulli Dropout for Bayesian Deep Learning. AISTATS 2020: 3905-3916 - [c68]Qing Jin, Linjie Yang, Zhenyu Liao, Xiaoning Qian:
Neural Network Quantization with Scale-Adjusted Training. BMVC 2020 - [c67]Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian:
Arsm Gradient Estimator for Supervised Learning to Rank. ICASSP 2020: 3157-3161 - [c66]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. ICASSP 2020: 3342-3346 - [c65]Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian:
NADS: Neural Architecture Distribution Search for Uncertainty Awareness. ICML 2020: 356-366 - [c64]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. ICML 2020: 4094-4104 - [c63]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: 10608-10615 - [c62]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. NeurIPS 2020 - [c61]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: 540-549 - [i21]Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Learnable Bernoulli Dropout for Bayesian Deep Learning. CoRR abs/2002.05155 (2020) - [i20]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 abs/2003.01753 (2020) - [i19]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 abs/2005.10477 (2020) - [i18]Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian:
Bayesian Graph Neural Networks with Adaptive Connection Sampling. CoRR abs/2006.04064 (2020) - [i17]Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian:
NADS: Neural Architecture Distribution Search for Uncertainty Awareness. CoRR abs/2006.06646 (2020) - [i16]Byung-Jun Yoon, Xiaoning Qian, Edward R. Dougherty:
Quantifying the multi-objective cost of uncertainty. CoRR abs/2010.04653 (2020) - [i15]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Xiaoning Qian:
BayReL: Bayesian Relational Learning for Multi-omics Data Integration. CoRR abs/2010.05895 (2020)
2010 – 2019
- 2019
- [j68]Shahin Boluki, Xiaoning Qian, Edward R. Dougherty:
Experimental Design via Generalized Mean Objective Cost of Uncertainty. IEEE Access 7: 2223-2230 (2019) - [j67]Chun-Chi Chen, Xiaoning Qian, Byung-Jun Yoon:
RNAdetect: efficient computational detection of novel non-coding RNAs. Bioinform. 35(7): 1133-1141 (2019) - [j66]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Bayesian negative binomial regression for differential expression with confounding factors. Bioinform. 35(13): 2346 (2019) - [j65]Chun-Chi Chen, Hyundoo Jeong, Xiaoning Qian, Byung-Jun Yoon:
TOPAS: network-based structural alignment of RNA sequences. Bioinform. 35(17): 2941-2948 (2019) - [j64]Byung-Jun Yoon, Xiaoning Qian, Tamer Kahveci, Ranadip Pal:
Selected research articles from the 2018 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC). BMC Bioinform. 20-S(12): 316:1-316:3 (2019) - [j63]Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty:
Optimal clustering with missing values. BMC Bioinform. 20-S(12): 321:1-321:10 (2019) - [j62]Kai He, Shuai Huang, Xiaoning Qian:
Early detection and risk assessment for chronic disease with irregular longitudinal data analysis. J. Biomed. Informatics 96 (2019) - [j61]Tianshu Feng, Xiaoning Qian, Kaibo Liu, Shuai Huang:
Dynamic Inspection of Latent Variables in State-Space Systems. IEEE Trans Autom. Sci. Eng. 16(3): 1232-1243 (2019) - [j60]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): 524-537 (2019) - [j59]Chung-Chi Tsai, Weizhi Li, Kuang-Jui Hsu, Xiaoning Qian, Yen-Yu Lin:
Image Co-Saliency Detection and Co-Segmentation via Progressive Joint Optimization. IEEE Trans. Image Process. 28(1): 56-71 (2019) - [c60]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: 266-275 - [c59]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: 8924-8933 - [c58]Xiaoqian Jia, Sicheng Wang, Xiao Liang, Anjali Balagopal, Dan Nguyen, Ming Yang, Zhangyang Wang, Jim Xiuquan Ji, Xiaoning Qian, Steve B. Jiang:
Cone-Beam Computed Tomography (CBCT) Segmentation by Adversarial Learning Domain Adaptation. MICCAI (6) 2019: 567-575 - [c57]Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. NeurIPS 2019: 10700-10710 - [c56]Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. NeurIPS 2019: 10711-10722 - [i14]Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. CoRR abs/1901.02427 (2019) - [i13]Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian, Edward R. Dougherty:
Optimal Clustering with Missing Values. CoRR abs/1902.09694 (2019) - [i12]Wuyang Chen, Ziyu Jiang, Zhangyang Wang, Kexin Cui, Xiaoning Qian:
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images. CoRR abs/1905.06368 (2019) - [i11]Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Graph Variational Auto-Encoders. CoRR abs/1908.07078 (2019) - [i10]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Variational Graph Recurrent Neural Networks. CoRR abs/1908.09710 (2019) - [i9]Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R. Narayanan, Mingyuan Zhou, Xiaoning Qian:
Semi-Implicit Stochastic Recurrent Neural Networks. CoRR abs/1910.12819 (2019) - [i8]Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian:
ARSM Gradient Estimator for Supervised Learning to Rank. CoRR abs/1911.00465 (2019) - 2018
- [j58]Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian:
Covariate-dependent negative binomial factor analysis of